The Effects of Ultracentrifuging Germinating Seeds of Onion and Rye

Normally, the process of mitosis is an orderly, integrated series of events, that is, karyokinesis and cytokinesis are usually linked together and function as one continuous process. Occasionally, however, either one or both of these processes may be interfered with in some way so that a dissociation takes place between the two. This gives rise to an abnormal situation so that each process may proceed independently of the other or one may be inhibited while the other goes on uninterrupted. The most common abnormal condition of this type is the inhibition of cell cleavage while nuclear division continues, resulting in the production of polyploids. This occurs rarely as a natural phenomenon, but more frequently as the result of disease, or quite commonly under experimental conditions. A few of the experimental agents used for inducing modification or inhibition of cell division are injury, heat, cold, ultraviolet and X-radiations, narcotics, anesthetics, hypertonic and hypotonic solutions, colchicine, and high centrifugal forces

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 - 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

Evolutionary instability of selfish learning in repeated games

Across many domains of interaction, both natural and artificial, individuals use past experience to shape future behaviors. The results of such learning processes depend on what individuals wish to maximize. A natural objective is one’s own success. However, when two such “selfish” learners interact with each other, the outcome can be detrimental to both, especially when there are conflicts of interest. Here, we explore how a learner can align incentives with a selfish opponent. Moreover, we consider the dynamics that arise when learning rules themselves are subject to evolutionary pressure. By combining extensive simulations and analytical techniques, we demonstrate that selfish learning is unstable in most classical two-player repeated games. If evolution operates on the level of long-run payoffs, selection instead favors learning rules that incorporate social (other-regarding) preferences. To further corroborate these results, we analyze data from a repeated prisoner’s dilemma experiment. We find that selfish learning is insufficient to explain human behavior when there is a trade-off between payoff maximization and fairness

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

The overlooked potential of Generalized Linear Models in astronomy-II: Gamma regression and photometric redshifts

Machine learning techniques offer a precious tool box for use within astronomy to solve problems involving so-called big data. They provide a means to make accurate predictions about a particular system without prior knowledge of the underlying physical processes of the data. In this article, and the companion papers of this series, we present the set of Generalized Linear Models (GLMs) as a fast alternative method for tackling general astronomical problems, including the ones related to the machine learning paradigm. To demonstrate the applicability of GLMs to inherently positive and continuous physical observables, we explore their use in estimating the photometric redshifts of galaxies from their multi-wavelength photometry. Using the gamma family with a log link function we predict redshifts from the PHoto-z Accuracy Testing simulated catalogue and a subset of the Sloan Digital Sky Survey from Data Release 10. We obtain fits that result in catastrophic outlier rates as low as ~1% for simulated and ~2% for real data. Moreover, we can easily obtain such levels of precision within a matter of seconds on a normal desktop computer and with training sets that contain merely tho nds of galaxies. Our software is made publicly available as a user-friendly package developed in Python, R and via an interactive web application. This software allows users to apply a set of GLMs to their own photometric catalogues and generates publication quality plots with minimum effort. By facilitating their ease of use to the astronomical community, this paper series aims to make GLMs widely known and to encourage their implementation in future large-scale projects, such as the Large Synoptic Survey Telescope

Differences in the Phosphatase Systems of Plant and Animal Tissue by a Michrotechnic

Gomori1 has shown the location of phosphatase m animal organs by a michrotechnic. The principle is as follows: tissue sections are incubated in the presence of a substrate. Phosphate ions will be split off by the enzyme and in the presence of the calcium ion will form insoluble calcium phosphate at the point of liberation. Calcium phosphate can be converted to a dark colored insoluble precipitate. The visible precipitate then indicates the location of the phosphatase. The purpose of this research has been to subject the plant material to a similar procedure and so demonstrate any similarity or dissimilarity to what is known concerning animal material

A Study of Preserved Blood Specimens Taken for Alcohol Determination

From the beginning of our experience with blood alcohol determinations for evidence in legal cases we have been called upon for information concerning the change of alcohol content in blood specimens after they have been drawn. Samples usually come to this laboratory in chemically clean glass vials stoppered with new corks and containing sufficient dry potassium oxalate to prevent clotting. These containers are obtained ready for use from this laboratory by county officials. However, many blood samples received have been contained otherwise, and often the temperature treatment of the specimens has not been uniform. To have available information about the probability that samples at the time of analysis contained the same amount of alcohol as at the time of drawing we performed suitable determinations, the results of which are presented here

A possible case of caprine-associated malignant catarrhal fever in a domestic water buffalo (Bubalus bubalis) in Switzerland

ABSTRACT: BACKGROUND: Malignant catarrhal fever (MCF) is a fatal herpesvirus infection, affecting various wild and domestic ruminants all over the world. Water buffaloes were reported to be particularly susceptible for the ovine herpesvirus-2 (OvHV-2) causing the sheep-associated form of MCF (SA-MCF). This report describes the first case of possibly caprine-associated malignant catarrhal fever symptoms in a domestic water buffalo in Switzerland. CASE PRESENTATION: The buffalo cow presented with persistent fever, dyspnoea, nasal bleeding and haematuria. Despite symptomatic therapy, the buffalo died and was submitted to post mortem examination. Major findings were an abomasal ulceration, a mild haemorrhagic cystitis and multifocal haemorrhages on the epicardium and on serosal and mucosal surfaces. Eyes and oral cavity were not affected. Histopathology revealed a mild to moderate lymphohistiocytic vasculitis limited to the brain and the urinary bladder. Although these findings are typical for MCF, OvHV-2 DNA was not detected in peripheral blood lymphocytes or in paraffin-embedded brain, using an OvHV-2 specific real time PCR. With the aid of a panherpesvirus PCR, a caprine herpesvirus-2 (CpHV-2) sequence could be amplified from both samples. CONCLUSIONS: To our knowledge, this is the first report of malignant catarrhal fever in the subfamily Bovinae, where the presence of CpHV-2 could be demonstrated. The etiological context has yet to be evaluated