Gas and dust in the Beta Pictoris Moving Group as seen by the Herschel Space Observatory

Context. Debris discs are thought to be formed through the collisional grinding of planetesimals, and can be considered as the outcome of planet formation. Understanding the properties of gas and dust in debris discs can help us to comprehend the architecture of extrasolar planetary systems. Herschel Space Observatory far-infrared (IR) photometry and spectroscopy have provided a valuable dataset for the study of debris discs gas and dust composition. This paper is part of a series of papers devoted to the study of Herschel PACS observations of young stellar associations. Aims. This work aims at studying the properties of discs in the Beta Pictoris Moving Group (BPMG) through far-IR PACS observations of dust and gas. Methods. We obtained Herschel-PACS far-IR photometric observations at 70, 100 and 160 microns of 19 BPMG members, together with spectroscopic observations of four of them. Spectroscopic observations were centred at 63.18 microns and 157 microns, aiming to detect [OI] and [CII] emission. We incorporated the new far-IR observations in the SED of BPMG members and fitted modified blackbody models to better characterise the dust content. Results. We have detected far-IR excess emission toward nine BPMG members, including the first detection of an IR excess toward HD 29391.The star HD 172555, shows [OI] emission, while HD 181296, shows [CII] emission, expanding the short list of debris discs with a gas detection. No debris disc in BPMG is detected in both [OI] and [CII]. The discs show dust temperatures in the range 55 to 264 K, with low dust masses (6.6*10^{-5} MEarth to 0.2 MEarth) and radii from blackbody models in the range 3 to 82 AU. All the objects with a gas detection are early spectral type stars with a hot dust component.Comment: 12 pages, 7 figures, 6 table

Finding a Needle in the Haystack: A Technique for Ranking Matches Between Components

Abstract. Searching and subsequently selecting reusable components from com-ponent repositories has become a key impediment for not only component-based development but also for achieving the overall usability of component develop-ment environments and the ultimate re-usability of the components themselves. Component matching, a fundamental aspect of the component search problem, has been a well-studied problem, resulting in many different matching technique

Factor and Simplex Models for Repeated Measures: Application to Two Psychomotor Measures of Alcohol Sensitivity in Twins

As part of a larger study, data on arithmetic computation and motor coordination were obtained from 206 twin pairs. The twins were measured once before and three times after ingesting a standard dose of alcohol. Previous analyses ignored the time-series structure of these data. Here we illustrate the application of simplex models for the genetic analysis of covariance structures in a repeated-measures design and compare the results with factor models for the two psychomotor measures. We then present a bivariate analysis incorporating simplex processes common and specific to the two measures. Our analyses confirm the notion that there is genetic variation affecting psychomotor performance which is "switched on" in the presence of alcohol. We compare the merits of analysis of mean products versus covariance matrices and confront some practical problems that may arise in situations where the number of subjects is relatively small and where the causal structure among the latent variables places a heavy demand on the data. © 1989 Plenum Publishing Corporation

State and dynamical parameter estimation for open quantum systems

Following the evolution of an open quantum system requires full knowledge of its dynamics. In this paper we consider open quantum systems for which the Hamiltonian is ``uncertain''. In particular, we treat in detail a simple system similar to that considered by Mabuchi [Quant. Semiclass. Opt. 8, 1103 (1996)]: a radiatively damped atom driven by an unknown Rabi frequency $\Omega$ (as would occur for an atom at an unknown point in a standing light wave). By measuring the environment of the system, knowledge about the system state, and about the uncertain dynamical parameter, can be acquired. We find that these two sorts of knowledge acquisition (quantified by the posterior distribution for $\Omega$, and the conditional purity of the system, respectively) are quite distinct processes, which are not strongly correlated. Also, the quality and quantity of knowledge gain depend strongly on the type of monitoring scheme. We compare five different detection schemes (direct, adaptive, homodyne of the $x$ quadrature, homodyne of the $y$ quadrature, and heterodyne) using four different measures of the knowledge gain (Shannon information about $\Omega$, variance in $\Omega$, long-time system purity, and short-time system purity).Comment: 14 pages, 18 figure

Phase II Trial of Cediranib in Combination With Cisplatin and Pemetrexed in Chemotherapy-Naïve Patients With Unresectable Malignant Pleural Mesothelioma (SWOG S0905).

PurposeAntiangiogenic agents combined with chemotherapy have efficacy in the treatment of unresectable malignant pleural mesothelioma (MPM). Cediranib (AstraZeneca, Cheshire, United Kingdom), a vascular endothelial growth factor receptor and platelet-derived growth factor receptor inhibitor, demonstrated therapeutic potential in a prior phase I trial. We evaluated a phase II trial for efficacy.Patients and methodsSWOG S0905 (ClinicalTrials.gov identifier: NCT01064648) randomly assigned cediranib or placebo with platinum-pemetrexed for six cycles followed by maintenance cediranib or placebo in unresectable chemotherapy-naïve patients with MPM of any histologic subtype. Primary end point was Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 progression-free survival (PFS). Secondary end points included overall survival, PFS by modified RECIST v1.1, response (modified RECIST and RECIST v1.1), disease control, and safety/toxicity. The trial was designed to detect a difference in RECIST v1.1 PFS at the one-sided 0.1 level using a stratified log-rank test.ResultsNinety-two eligible patients were enrolled (75% epithelioid and 25% biphasic or sarcomatoid). The cediranib arm had more grade 3 and 4 diarrhea, dehydration, hypertension, and weight loss. Cediranib improved PFS by RECIST v1.1 (hazard ratio, 0.71; 80% CI, 0.54 to 0.95; P = .062; 7.2 months v 5.6 months) and increased modified RECIST v1.1 response (50% v 20%; P = .006). By modified RECIST v1.1, cediranib numerically increased PFS (hazard ratio, 0.77; 80% CI, 0.59 to 1.02; P = .12; median, 6.9 months v 5.6 months). No significant difference in overall survival was observed.ConclusionThe addition of cediranib to platinum-pemetrexed improved PFS by RECIST v1.1 and response rate by modified RECIST in patients with unresectable MPM. Whereas adding antiangiogenics to chemotherapy has been a successful strategy for some patients, the cediranib toxicity profile and small incremental survival benefit precludes additional development in MPM

How predation and landscape fragmentation affect vole population dynamics

Background: Microtine species in Fennoscandia display a distinct north-south gradient from regular cycles to stable populations. The gradient has often been attributed to changes in the interactions between microtines and their predators. Although the spatial structure of the environment is known to influence predator-prey dynamics of a wide range of species, it has scarcely been considered in relation to the Fennoscandian gradient. Furthermore, the length of microtine breeding season also displays a north-south gradient. However, little consideration has been given to its role in shaping or generating population cycles. Because these factors covary along the gradient it is difficult to distinguish their effects experimentally in the field. The distinction is here attempted using realistic agent-based modelling. Methodology/Principal Findings: By using a spatially explicit computer simulation model based on behavioural and ecological data from the field vole (Microtus agrestis), we generated a number of repeated time series of vole densities whose mean population size and amplitude were measured. Subsequently, these time series were subjected to statistical autoregressive modelling, to investigate the effects on vole population dynamics of making predators more specialised, of altering the breeding season, and increasing the level of habitat fragmentation. We found that fragmentation as well as the presence of specialist predators are necessary for the occurrence of population cycles. Habitat fragmentation and predator assembly jointly determined cycle length and amplitude. Length of vole breeding season had little impact on the oscillations. Significance: There is good agreement between our results and the experimental work from Fennoscandia, but our results allow distinction of causation that is hard to unravel in field experiments. We hope our results will help understand the reasons for cycle gradients observed in other areas. Our results clearly demonstrate the importance of landscape fragmentation for population cycling and we recommend that the degree of fragmentation be more fully considered in future analyses of vole dynamics

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Evidence of Isotopic Fractionation During Vapor Exchange Between the Atmosphere and the Snow Surface in Greenland

Several recent studies from both Greenland and Antarctica have reported significant changes in the water isotopic composition of near‐surface snow between precipitation events. These changes have been linked to isotopic exchange with atmospheric water vapor and sublimation‐induced fractionation, but the processes are poorly constrained by observations. Understanding and quantifying these processes are crucial to both the interpretation of ice core climate proxies and the formulation of isotope‐enabled general circulation models. Here, we present continuous measurements of the water isotopic composition in surface snow and atmospheric vapor together with near‐surface atmospheric turbulence and snow‐air latent and sensible heat fluxes, obtained at the East Greenland Ice‐Core Project drilling site in summer 2016. For two 4‐day‐long time periods, significant diurnal variations in atmospheric water isotopologues are observed. A model is developed to explore the impact of this variability on the surface snow isotopic composition. Our model suggests that the snow isotopic composition in the upper subcentimeter of the snow exhibits a diurnal variation with amplitudes in δ18O and δD of ~2.5‰ and ~13‰, respectively. As comparison, such changes correspond to 10–20% of the magnitude of seasonal changes in interior Greenland snow pack isotopes and of the change across a glacial‐interglacial transition. Importantly, our observation and model results suggest, that sublimation‐induced fractionation needs to be included in simulations of exchanges between the vapor and the snow surface on diurnal timescales during summer cloud‐free conditions in northeast Greenland

Mutational Specificity of γ-Radiation-Induced Guanine−Thymine and Thymine−Guanine Intrastrand Cross-Links in Mammalian Cells and Translesion Synthesis Past the Guanine−Thymine Lesion by Human DNA Polymerase η†

ABSTRACT: Comparative mutagenesis of γ- or X-ray-induced tandem DNA lesions G[8,5-Me]T and T[5-Me,8]G intrastrand cross-links was investigated in simian (COS-7) and human embryonic (293T) kidney cells. For G[8,5-Me]T in 293T cells, 5.8 % of progeny contained targeted base substitutions, whereas 10.0 % showed semitargeted single-base substitutions. Of the targeted mutations, the G f T mutation occurred with the highest frequency. The semitargeted mutations were detected up to two bases 5 ′ and three bases 3 ′ to the cross-link. The most prevalent semitargeted mutation was a C f T transition immediately 5 ′ to the G[8,5-Me]T cross-link. Frameshifts (4.6%) (mostly small deletions) and multiple-base substitutions (2.7%) also were detected. For the T[5-Me,8]G cross-link, a similar pattern of mutations was noted, but the mutational frequency was significantly higher than that of G[8,5-Me]T. Both targeted and semitargeted mutations occurred with a frequency of ∼16%, and both included a dominant G f T transversion. As in 293T cells, more than twice as many targeted mutations in COS cells occurred in T[5-Me,8]G (11.4%) as in G[8,5-Me]T (4.7%). Also, the level of semitargeted single-base substitutions 5 ′ to the lesion was increased and 3 ′ to the lesion decreased in T[5-Me,8]G relative to G[8,5-Me]T in COS cells. It appeared that the majority of the base substitutions at or near the cross-links resulted from incorporation of dAMP opposite the template base, in agreement with the so-called “A-rule”. To determin