Bayesian salamanders: analysing the demography of an underground population of the European plethodontid <i>Speleomantes strinatii</i> with state-space modelling

&lt;b&gt;Background&lt;/b&gt;: It has been suggested that Plethodontid salamanders are excellent candidates for indicating ecosystem health. However, detailed, long-term data sets of their populations are rare, limiting our understanding of the demographic processes underlying their population fluctuations. Here we present a demographic analysis based on a 1996 - 2008 data set on an underground population of Speleomantes strinatii (Aellen) in NW Italy. We utilised a Bayesian state-space approach allowing us to parameterise a stage-structured Lefkovitch model. We used all the available population data from annual temporary removal experiments to provide us with the baseline data on the numbers of juveniles, subadults and adult males and females present at any given time. &lt;b&gt;Results&lt;/b&gt;: Sampling the posterior chains of the converged state-space model gives us the likelihood distributions of the state-specific demographic rates and the associated uncertainty of these estimates. Analysing the resulting parameterised Lefkovitch matrices shows that the population growth is very close to 1, and that at population equilibrium we expect half of the individuals present to be adults of reproductive age which is what we also observe in the data. Elasticity analysis shows that adult survival is the key determinant for population growth. &lt;b&gt;Conclusion&lt;/b&gt;: This analysis demonstrates how an understanding of population demography can be gained from structured population data even in a case where following marked individuals over their whole lifespan is not practical

Modular Autoencoders for Ensemble Feature Extraction

We introduce the concept of a Modular Autoencoder (MAE), capable of learning a set of diverse but complementary representations from unlabelled data, that can later be used for supervised tasks. The learning of the representations is controlled by a trade off parameter, and we show on six benchmark datasets the optimum lies between two extremes: a set of smaller, independent autoencoders each with low capacity, versus a single monolithic encoding, outperforming an appropriate baseline. In the present paper we explore the special case of linear MAE, and derive an SVD-based algorithm which converges several orders of magnitude faster than gradient descent.Comment: 18 pages, 8 figures, to appear in a special issue of The Journal Of Machine Learning Research (vol.44, Dec 2015

Classification with unknown class-conditional label noise on non-compact feature spaces

We investigate the problem of classification in the presence of unknown class-conditional label noise in which the labels observed by the learner have been corrupted with some unknown class dependent probability. In order to obtain finite sample rates, previous approaches to classification with unknown class-conditional label noise have required that the regression function is close to its extrema on sets of large measure. We shall consider this problem in the setting of non-compact metric spaces, where the regression function need not attain its extrema. In this setting we determine the minimax optimal learning rates (up to logarithmic factors). The rate displays interesting threshold behaviour: When the regression function approaches its extrema at a sufficient rate, the optimal learning rates are of the same order as those obtained in the label-noise free setting. If the regression function approaches its extrema more gradually then classification performance necessarily degrades. In addition, we present an adaptive algorithm which attains these rates without prior knowledge of either the distributional parameters or the local density. This identifies for the first time a scenario in which finite sample rates are achievable in the label noise setting, but they differ from the optimal rates without label noise

RNA Polymerase-Binding and Transcription Initiation Sites Upstream of the Methyl Reductase Operon of Methanococcus vannielii

RNA Polymerase, purified from Methanococcus vannielii, was shown by exonuclease III footprinting to bind to a 49-base-pair (bp) region of DNA in the intergenic region upstream of mcrB. Sl nuclease protection experiments demonstrated that transcription Initiation in vivo occurs within this region at 32 or 33 bp 5' to the A T G translation initiation codon of mcrB and 19 or 20 bp 3' to a T A T A box

Exclusionary Discipline Highest in New Hampshire’s Urban Schools Suspension and Expulsion Found to Disproportionately Affect Disadvantaged Students

This research brief follows up on a joint Carsey/NH Kids Count publication from 2009. The 2009 study focused on larger disciplinary trends in New Hampshire schools and contextualized them in the policies, laws, and procedures that may have resulted in increased use of exclusionary discipline. The present study reports on rates of exclusionary discipline from 2010 through 2014 by school and student characteristics to better understand how and to what extent exclusionary discipline has been applied across the state in recent years. Authors Douglas Gagnon, Eleanor Jaffee, and Reeve Kennedy report that although rates of out-of-school suspension among secondary school students in New Hampshire are nearly as high as national trends, rates of expulsion are far below the national average. In urban secondary schools, the rate of in-school suspension is twice that of non-urban schools, while out-of-school suspension rates are three times higher. Male students, students of color, students eligible for free or reduced-price lunch, students with disabilities, and homeless students are more likely to experience exclusionary school discipline, although racial disparities appear to stem largely from the greater racial diversity at the urban schools that use this type of discipline at higher rates with all students. Statewide, 3.5 percent of New Hampshire’s middle and high school students are suspended out of school for a total of five days or more and/or expelled in a given year. Given the notably higher rates of use of exclusionary discipline in New Hampshire’s urban school districts, the authors recommend that school policies and environments be assessed for opportunities to reverse these trends and provide more students with consistent classroom time and instruction

SpinLink: An interconnection system for the SpiNNaker biologically inspired multi-computer

SpiNNaker is a large-scale biologically-inspired multi-computer designed to model very heavily distributed problems, with the flagship application being the simulation of large neural networks. The project goal is to have one million processors included in a single machine, which consequently span many thousands of circuit boards. A computer of this scale imposes large communication requirements between these boards, and requires an extensible method of connecting to external equipment such as sensors, actuators and visualisation systems. This paper describes two systems that can address each of these problems.Firstly, SpinLink is a proposed method of connecting the SpiNNaker boards by using time-division multiplexing (TDM) to allow eight SpiNNaker links to run at maximum bandwidth between two boards. SpinLink will be deployed on Spartan-6 FPGAs and uses a locally generated clock that can be paused while the asynchronous links from SpiNNaker are sending data, thus ensuring a fast and glitch-free response. Secondly, SpiNNterceptor is a separate system, currently in the early stages of design, that will build upon SpinLink to address the important external I/O issues faced by SpiNNaker. Specifically, spare resources in the FPGAs will be used to implement the debugging and I/O interfacing features of SpiNNterceptor

Physiotherapy interventions to prevent postoperative pulmonary complications following lung resection. What is the evidence? What is the practice?

Following major surgery pulmonary complications are an important cause of postoperative morbidity, contributing to significant increases in length of hospital stay, overall hospital costs and patient discomfort. Physiotherapy aims to prevent and treat pulmonary complications and a number of high quality studies have investigated the efficacy of various physiotherapy interventions in major surgical populations, particularly following cardiac and upper abdominal surgery. To date, however, there have been few studies investigating the effectiveness of physiotherapy interventions in patients undergoing lung surgery via thoracotomy. This paper reviews the limited evidence investigating physiotherapy interventions aimed at preventing postoperative pulmonary complications following lung resection, considers current physiotherapy management for this patient group and makes recommendations for future practice and research