Optimized supernova constraints on dark energy evolution

A model-independent method to study the possible evolution of dark energy is presented. Optimal estimates of the dark energy equation of state w are obtained from current supernovae data from Riess et al. (2004) following a principal components approach. We assess the impact of varying the number of piecewise constant estimates of w using a model selection method, the Bayesian information criterion, and compare the most favored models with some parametrizations commonly used in the literature. Although data seem to prefer a cosmological constant, some models are only moderately disfavored by our selection criterion: a constant w, w linear in the scale factor, w linear in redshift and the two-parameter models introduced here. Among these, the models we find by optimization are slightly preferred. However, current data do not allow us to draw a conclusion on the possible evolution of dark energy. Interestingly, the best fits for all varying-w models exhibit a w<-1 at low redshifts.Comment: 6 pages, 4 figures; typos removed and reference added to match published versio

Transarterielle Chemoembolisation als Selektionsmarker für Patienten mit HCC vor LTX unter retrospektiver Zuhilfenahme histologischer Ergebnisse [meeting abstract]

Einleitung: Für die meisten Patienten mit HCC ist die LTX die einzige kurative Behandlungsoption. Bei diesen Patienten scheint eine Kontrolle der Erkrankung durch lokale Verfahren im Intervall bis zur LTX zu erreichen zu sein. Als das beste Verfahren gilt die transarterielle Chemoembolisation (TACE). Die Effektivität ist jedoch umstritten. Möglicherweise kann sie aber Patienten startifizieren, die ein hohes Rezidivrisiko haben. Material und Methoden: Im Zeitraum zwischen 1995 und 2005 wurden n=27 Patienten mit HCC im Alter zwischen 22 und 69 Jahren transplantiert. Hiervon erhielten n=15 Patienten eine Vorbehandlung in Form einer alleinigen TACE oder kombiniert mit PEI [n=1] bzw. LITT [n=1]. Retrospektiv wurde das Gesamtüberleben sowie das „Event-free-survival“ (Rezidiv, Reinfektion und Tod) analysiert. Ergebnisse: Die mittlere Wartezeit betrug bei Patienten in der TACE-Gruppe 214 Tage, bei Patienten ohne Vorbehandlung 133 Tage. Bei einem mittleren Nachbeobachtungszeitraum von 1097 ± 1193 Tagen für TACE-Patienten und 1674 ± 966 Tagen für non-TACE-Patienten betrug das Überleben für Patienten, die mit TACE vorbehandelt wurden 83,3%, für Patienten, die keine TACE erhielten 86.7% (p=0,5693). Gleiches fand sich für das Event-free-survival (p=0,8823). Das Gesamtüberleben der Patienten, die auf der Warteliste einen Tumorprogress hatten lag bei 77%, während Patienten mit stabiler Tumorgröße oder Regredienz der Tumore ein Überleben von 93% aufwiesen (p=0,0153). Unter TACE-Behandlung zeigten 5/15 Patienten eine zunehmende Anzahl an Herden im histologischen Präparat verglichen mit der Ausgangsbildgebung. Nur bei einem Patienten zeigte sich der Progress der Erkrankung bereits in der präoperativen Bildgebung. Patienten mit einem Progress der Erkrankung hatten ein Gesamtüberleben von 60%, während Patienten mit „stable disease“ oder Rückgang der Herde ein Gesamtüberleben von 100% hatten (p=0,0180). Schlussfolgerung: Unseren Ergebnisse zufolge ist der Effekt der TACE als Bridgingverfahren auf das Überleben der Patienten fraglich. Allerdings scheint die TACE zur Riskostratifizierung geeignet zu sein. In unserem Patientenkollektiv hatten Patienten, die eine Progredienz der Erkrankung auf der Warteliste zeigten ein signifikant schlechteres Gesamtüberleben. Dies gilt auch bei ausschließlicher Betrachtung der Patienten mit TACE

Response of ‘pérola’ pineapple to five planting dates

Objetivando estudar o efeito da época de plantio sobre a produção do abacaxizeiro (Ananas comosus (L.) Merrill) cv. Pérola, efetuou-se, nas primeiras quinzenas de setembro a dezembro de 1981 e janeiro de 1982, na Estação Experimental de Águas Belas, situada no município de Viamão, RS, o plantio de mudas, pesando de 120 a 200 gramas. O ciclo natural, do plantio à colheita, diminuiu, em média, 50 dias, com o atraso do plantio de setembro para dezembro. A indução floral natural ocorreu sempre no primeiro inverno após o plantio. A colheita dos frutos se estendeu de fevereiro a abril de 1983. A antecipação do plantio aumentou o rendimento, por unidade de área, tamanho do fruto, peso médio do fruto e proporção de frutos com mais de 900 g, ao passo que o retardamento da época de plantio aumentou a proporção de frutos com 600 g a 900 g.An experiment was carried out at the "Estação Experimental de Águas Belas" at Viamão, RS, Brazil, to study the effect of planting dates on the yield of pineapple (Ananas comosus (L.) Merrill) cv. Pérola. Pineapple slips weighing 120 g to 200 g each were planted on the first fortnights of September through December 1981 and January 1982. Delayed planting date from September throug December and January caused a 50-day decrease in the natural crop cycle. Flowering induction occurred every first Winter after planting. Fruits were harvested from February through April 1983. Early planting caused an increase in yield size and weight of fruits as well as in the percentage of fruits heavier than 900 g. Delayed planting caused increase only in the percentage of fruits ranging from 600 to 900 in weight.

Modeling violations of the race model inequality in bimodal paradigms: co-activation from decision and non-decision components

The redundant-signals paradigm (RSP) is designed to investigate response behavior in perceptual tasks in which response-relevant targets are defined by either one or two features, or modalities. The common finding is that responses are speeded for redundantly compared to singly defined targets. This redundant-signals effect (RSE) can be accounted for by race models if the response times do not violate the race model inequality (RMI). When there are violations of the RMI, race models are effectively excluded as a viable account of the RSE. The common alternative is provided by co-activation accounts, which assume that redundant target signals are integrated at some processing stage. However, “co-activation” has mostly been only indirectly inferred and the accounts have only rarely been explicitly modeled; if they were modeled, the RSE has typically been assumed to have a decisional locus. Yet, there are also indications in the literature that the RSE might originate, at least in part, at a non-decisional or motor stage. In the present study, using a distribution analysis of sequential-sampling models (ex-Wald and Ratcliff Diffusion model), the locus of the RSE was investigated for two bimodal (audio-visual) detection tasks that strongly violated the RMI, indicative of substantial co-activation. Three model variants assuming different loci of the RSE were fitted to the quantile reaction time proportions: a decision, a non-decision, and a combined variant both to vincentized group as well as individual data. The results suggest that for the two bimodal detection tasks, co-activation has a shared decisional and non-decisional locus. These findings point to the possibility that the mechanisms underlying the RSE depend on the specifics (task, stimulus, conditions, etc.) of the experimental paradigm

Accelerated expansion from structure formation

We discuss the physics of backreaction-driven accelerated expansion. Using the exact equations for the behaviour of averages in dust universes, we explain how large-scale smoothness does not imply that the effect of inhomogeneity and anisotropy on the expansion rate is small. We demonstrate with an analytical toy model how gravitational collapse can lead to acceleration. We find that the conjecture of the accelerated expansion being due to structure formation is in agreement with the general observational picture of structures in the universe, and more quantitative work is needed to make a detailed comparison.Comment: 44 pages, 1 figure. Expanded treatment of topics from the Gravity Research Foundation contest essay astro-ph/0605632. v2: Added references, clarified wordings. v3: Published version. Minor changes and corrections, added a referenc

Identifying chemical aerosol signatures using optical suborbital observations: how much can optical properties tell us about aerosol composition

Improvements in air quality and Earth\u27s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine aerosol composition measurements from ground-based networks are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, an airborne field campaign carried out over the US during the summer of 2013). We find distinct optical signatures for AMTs such as biomass burning (from agricultural or wildfires), biogenic and polluted dust. We find that all four AMTs, studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from a few combinations of airborne in situ aerosol optical properties (e.g., extinction Ångström exponent, absorption Ångström exponent and real refractive index). However, we find that the optically based classifications for biomass burning from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results related to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol dataset to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosols, Cloud, Convection and Precipitation (ACCP) designated observables)

Statistical Guidance for Experimental Design and Data Analysis of Mutation Detection in Rare Monogenic Mendelian Diseases by Exome Sequencing

Recently, whole-genome sequencing, especially exome sequencing, has successfully led to the identification of causal mutations for rare monogenic Mendelian diseases. However, it is unclear whether this approach can be generalized and effectively applied to other Mendelian diseases with high locus heterogeneity. Moreover, the current exome sequencing approach has limitations such as false positive and false negative rates of mutation detection due to sequencing errors and other artifacts, but the impact of these limitations on experimental design has not been systematically analyzed. To address these questions, we present a statistical modeling framework to calculate the power, the probability of identifying truly disease-causing genes, under various inheritance models and experimental conditions, providing guidance for both proper experimental design and data analysis. Based on our model, we found that the exome sequencing approach is well-powered for mutation detection in recessive, but not dominant, Mendelian diseases with high locus heterogeneity. A disease gene responsible for as low as 5% of the disease population can be readily identified by sequencing just 200 unrelated patients. Based on these results, for identifying rare Mendelian disease genes, we propose that a viable approach is to combine, sequence, and analyze patients with the same disease together, leveraging the statistical framework presented in this work