The recoil transfer chamber - An interface to connect the physical preseparator TASCA with chemistry and counting setups

Performing experiments with transactinide elements demands highly sensitive detection methods due to the extremely low production rates (one-atom-at-a-time conditions). Preseparation with a physical recoil separator is a powerful method to significantly reduce the background in experiments with sufficiently long-lived isotopes (t1/2≥0.5 s). In the last years, the new gas-filled TransActinide Separator and Chemistry Apparatus (TASCA) was installed and successfully commissioned at GSI. Here, we report on the design and performance of a Recoil Transfer Chamber (RTC) for TASCA—an interface to connect various chemistry and counting setups with the separator. Nuclear reaction products recoiling out of the target are separated according to their magnetic rigidity within TASCA, and the wanted products are guided to the focal plane of TASCA. In the focal plane, they pass a thin Mylar window that separates the ∼1 mbar atmosphere in TASCA from the RTC kept at ∼1 bar. The ions are stopped in the RTC and transported by a continuous gas flow from the RTC to the ancillary setup. In this paper, we report on measurements of the transportation yields under various conditions and on the first chemistry experiments at TASCA—an electrochemistry experiment with osmium and an ion exchange experiment with the transactinide element rutherfordium.

The low-energy β− and electron emitter 161Tb as an alternative to 177Lu for targeted radionuclide therapy

The low-energy β− emitter 161Tb is very similar to 177Lu with respect to half-life, beta energy and chemical properties. However, 161Tb also emits a significant amount of conversion and Auger electrons. Greater therapeutic effect can therefore be expected in comparison to 177Lu. It also emits low-energy photons that are useful for gamma camera imaging. The 160Gd(n,γ)161Gd→161Tb production route was used to produce 161Tb by neutron irradiation of massive 160Gd targets (up to 40 mg) in nuclear reactors. A semiautomated procedure based on cation exchange chromatography was developed and applied to isolate no carrier added (n.c.a.) 161Tb from the bulk of the 160Gd target and from its stable decay product 161Dy. 161Tb was used for radiolabeling DOTA-Tyr3-octreotate; the radiolabeling profile was compared to the commercially available n.c.a. 177Lu. A 161Tb Derenzo phantom was imaged using a small-animal single-photon emission computed tomography camera. Up to 15 GBq of 161Tb was produced by long-term irradiation of Gd targets. Using a cation exchange resin, we obtained 80%–90% of the available 161Tb with high specific activity, radionuclide and chemical purity and in quantities sufficient for therapeutic applications. The 161Tb obtained was of the quality required to prepare 161Tb–DOTA-Tyr3-octreotate. We were able to produce 161Tb in n.c.a. form by irradiating highly enriched 160Gd targets; it can be obtained in the quantity and quality required for the preparation of 161Tb-labeled therapeutic agents.

Bivariate meta-analysis of predictive values of diagnostic tests can be an alternative to bivariate meta-analysis of sensitivity and specificity

Meta-analysis of predictive values is usually discouraged because these values are directly affected by disease prevalence, but sensitivity and specificity sometimes show substantial heterogeneity as well. We propose a bivariate random-effects logitnormal model for the meta-analysis of the positive predictive value (PPV) and negative predictive value (NPV) of diagnostic tests.

Reading Readings: An Approach to the Relationship between Television and Literature at School

The main problem addressed by this research was that of what are the relations between TV viewing at home and studying literature at school, and how an adequate position on this can be reached. As well as the theoretical background, it involved an experimental study with classes of second and sixth grade students, discussing and observing their reactions to and interpretations of a number of animated cartoons. The work is divided into four parts - Is there a Class in this Text?, Stories of Reading, Narratives of Animation and Animation of Narratives, and The (Three) Unrepeatable (Pigs). Beginning, Middle End - which examine the tensions between the "undiscriminating sequence" of the televisual flow and a way of "thinking", "making" and "doing" education that presupposes a fundamental belief in possible re-productions, copies unescaping, following the original, or competing. The work focuses on animated cartoons, seeing them not merely as a part of the flow of television, but as an allegory of reading this flow, of the flow within the flow itself. What they question - "identity", "end", "followability" - is what is most important to teaching. Thus the interest in the metamorphoses of animated films is an interest in the tensions which their "strange law/flow" introduces into the field of teaching - this totally forbidden place of saying everything.

Sustainable land management: A new approach to soil and water conservation in Ethiopia

Many efforts have been made in Ethiopia to mitigate land degradation, particularly soil erosion, through both local and newly introduced soil and water conservation (SWC) practices. However, the strict focus on soil erosion and conservation does not necessarily lead to satisfactory results. If SWC is effective in reducing erosion but is at the same time too costly and unacceptable to land users, sooner or later it will disappear and its positive effects will also be lost. This book therefore suggests to follow the broader approach of Sustainable Land Management (SLM), which aims at ecological soundness, economic viability and social acceptability, and thus places SWC in a more holistic framework that is closer to farmers’ reality.

An introduction to low-level analysis methods of DNA microarray data

This article gives an overview over the methods used in the low--level analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of nucleic acid abundance in a set of tissues or cell populations for thousands of transcripts or loci simultaneously. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. This includes the design of probes, the experimental design, the image analysis of microarray scanned images, the normalization of fluorescence intensities, the assessment of the quality of microarray data and incorporation of quality information in subsequent analyses, the combination of information across arrays and across sets of experiments, the discovery and recognition of patterns in expression at the single gene and multiple gene levels, and the assessment of significance of these findings, considering the fact that there is a lot of noise and thus random features in the data. For all of these components, access to a flexible and efficient statistical computing environment is an essential aspect.

Checking Assumptions in Latent Class Regression Models via a Markov Chain Monte Carlo Estimation Approach: An Application to Depression and Socio-Economic Status

Latent class regression models are useful tools for assessing associations between covariates and latent variables. However, evaluation of key model assumptions cannot be performed using methods from standard regression models due to the unobserved nature of latent outcome variables. This paper presents graphical diagnostic tools to evaluate whether or not latent class regression models adhere to standard assumptions of the model: conditional independence and non-differential measurement. An integral part of these methods is the use of a Markov Chain Monte Carlo estimation procedure. Unlike standard maximum likelihood implementations for latent class regression model estimation, the MCMC approach allows us to calculate posterior distributions and point estimates of any functions of parameters. It is this convenience that allows us to provide the diagnostic methods that we introduce. As a motivating example we present an analysis focusing on the association between depression and socioeconomic status, using data from the Epidemiologic Catchment Area study. We consider a latent class regression analysis investigating the association between depression and socioeconomic status measures, where the latent variable depression is regressed on education and income indicators, in addition to age, gender, and marital status variables. While the fitted latent class regression model yields interesting results, the model parameters are found to be invalid due to the violation of model assumptions. The violation of these assumptions is clearly identified by the presented diagnostic plots. These methods can be applied to standard latent class and latent class regression models, and the general principle can be extended to evaluate model assumptions in other types of models.

TRENDS IN PARTICULATE MATTER AND MORTALITY: AN APPROACH TO THE ASSESSMENT OF UNMEASURED CONFOUNDING

We propose a method for diagnosing confounding bias under a model which links a spatially and temporally varying exposure and health outcome. We decompose the association into orthogonal components, corresponding to distinct spatial and temporal scales of variation. If the model fully controls for confounding, the exposure effect estimates should be equal at the different temporal and spatial scales. We show that the overall exposure effect estimate is a weighted average of the scale-specific exposure effect estimates. We use this approach to estimate the association between monthly averages of fine particles (PM2.5) over the preceding 12 months and monthly mortality rates in 113 U.S. counties from 2000-2002. We decompose the association between PM2.5 and mortality into two components: 1) the association between “national trends” in PM2.5 and mortality; and 2) the association between “local trends,” defined as county-specificdeviations from national trends. This second component provides evidence as to whether counties having steeper declines in PM2.5 also have steeper declines in mortality relative to their national trends. We find that the exposure effect estimates are different at these two spatio-temporalscales, which raises concerns about confounding bias. We believe that the association between trends in PM2.5 and mortality at the national scale is more likely to be confounded than is the association between trends in PM2.5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality.