Observations of the northern seasonal polar cap on Mars: I. Spring sublimation activity and processes

Spring sublimation of the seasonal CO2 northern polar cap is a dynamic process in the current Mars climate. Phenomena include dark fans of dune material propelled out onto the seasonal ice layer, polygonal cracks in the seasonal ice, sand flow down slipfaces, and outbreaks of gas and sand around the dune margins. These phenomena are concentrated on the north polar erg that encircles the northern residual polar cap. The Mars Reconnaissance Orbiter has been in orbit for three Mars years, allowing us to observe three northern spring seasons. Activity is consistent with and well described by the Kieffer model of basal sublimation of the seasonal layer of ice applied originally in the southern hemisphere. Three typical weak spots have been identified on the dunes for escape of gas sublimed from the bottom of the seasonal ice layer: the crest of the dune, the interface of the dune with the interdune substrate, and through polygonal cracks in the ice. Pressurized gas flows through these vents and carries out material entrained from the dune. Furrows in the dunes channel gas to outbreak points and may be the northern equivalent of southern radially-organized channels ("araneiform" terrain), albeit not permanent. Properties of the seasonal CO2 ice layer are derived from timing of seasonal events such as when final sublimation occurs. Modification of dune morphology shows that landscape evolution is occurring on Mars today, driven by seasonal activity associated with sublimation of the seasonal CO2 polar cap.

State-of-the-art aortic imaging: part I - fundamentals and perspectives of CT and MRI

Over the last two decades, imaging of the aorta has undergone a clinically relevant change. As part of the change non-invasive imaging techniques have replaced invasive intra-arterial digital subtraction angiography as the former imaging gold standard for aortic diseases. Computed tomography (CT) and magnetic resonance imaging (MRI) constitute the backbone of pre- and postoperative aortic imaging because they allow for imaging of the entire aorta and its branches. The first part of this review article describes the imaging principles of CT and MRI with regard to aortic disease, shows how both technologies can be applied in every day clinical practice, offering exciting perspectives. Recent CT scanner generations deliver excellent image quality with a high spatial and temporal resolution. Technical developments have resulted in CT scan performed within a few seconds for the entire aorta. Therefore, CT angiography (CTA) is the imaging technology of choice for evaluating acute aortic syndromes, for diagnosis of most aortic pathologies, preoperative planning and postoperative follow-up after endovascular aortic repair. However, radiation dose and the risk of contrast induced nephropathy are major downsides of CTA. Optimisation of scan protocols and contrast media administration can help to reduce the required radiation dose and contrast media. MR angiography (MRA) is an excellent alternative to CTA for both diagnosis of aortic pathologies and postoperative follow-up. The lack of radiation is particularly beneficial for younger patients. A potential side effect of gadolinium contrast agents is nephrogenic systemic fibrosis (NSF). In patients with high risk of NSF unenhanced MRA can be performed with both ECG- and breath-gating techniques. Additionally, MRI provides the possibility to visualise and measure both dynamic and flow information.

Radiocarbon Analysis of Elemental and Organic Carbon in Switzerland during Winter-Smog Episodes from 2008 to 2012 – Part I: Source Apportionment and Spatial Variability

While several studies have investigated winter-time air pollution with a wide range of concentration levels, hardly any results are available for longer time periods covering several winter-smog episodes at various locations; e.g., often only a few weeks from a single winter are investigated. Here, we present source apportionment results of winter-smog episodes from 16 air pollution monitoring stations across Switzerland from five consecutive winters. Radiocarbon (14C) analyses of the elemental (EC) and organic (OC) carbon fractions, as well as levoglucosan, major water-soluble ionic species and gas-phase pollutant measurements were used to characterize the different sources of PM10. The most important contributions to PM10 during winter-smog episodes in Switzerland were on average the secondary inorganic constituents (sum of nitrate, sulfate and ammonium = 41 ± 15%) followed by organic matter (OM) (34 ± 13%) and EC (5 ± 2%). The non-fossil fractions of OC (fNF,OC) ranged on average from 69 to 85 and 80 to 95% for stations north and south of the Alps, respectively, showing that traffic contributes on average only up to ~ 30% to OC. The non-fossil fraction of EC (fNF,EC), entirely attributable to primary wood burning, was on average 42 ± 13 and 49 ± 15% for north and south of the Alps, respectively. While a high correlation was observed between fossil EC and nitrogen oxides, both primarily emitted by traffic, these species did not significantly correlate with fossil OC (OCF), which seems to suggest that a considerable amount of OCF is secondary, from fossil precursors. Elevated fNF,EC and fNF,OC values and the high correlation of the latter with other wood burning markers, including levoglucosan and water soluble potassium (K+) indicate that residential wood burning is the major source of carbonaceous aerosols during winter-smog episodes in Switzerland. The inspection of the non-fossil OC and EC levels and the relation with levoglucosan and water-soluble K+ shows different ratios for stations north and south of the Alps (most likely because of differences in burning technologies) for these two regions in Switzerland.

"Of course I will...": The combined effect of certainty and level of expectancies on persistence and performance

The importance of performance expectancies for the prediction of regulation of behavior and actual performance has long been established. Building on theories from the field of social cognition, we suggest that the level of performance expectancies, as well as the certainty of the expectancy, have a joint influence on an individual’s beliefs and behavior. In two studies (one cross sectional using a sample of secondary school students and one longitudinal using a sample of university students) we found that expectancies more strongly predicted persistence, and subsequent performance, the more certain the expectancy was. This pattern was found even if prior performance was controlled, as in Study 2. The data give an indication that it may be useful to include certainty as an additional variable in expectancy models.

Guidelines for WB3 Part I: Desertification and land degradation: Identification of existing and potential prevention and mitigation strategies

These guidelines are a working instrument for conducting and moderating stakeholder workshops with a participatory approach to initiate a mutual learning process among local and external stakeholders. The overall aim of the workshop is to identify promising (existing and potential) strategies for land and water conservation for the selected study site. DESIRE (Desertification Mitigation and Remediation of Land) is a European Integrated Project. The DESIRE WB 3 methodology was developed by CDE and is based on experiences from Learning for Sustainability (LforS) and WOCAT.

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

Shulamit an Ancient Love-Drama. Known as the "Song of Songs," and attributed to Solomon, King of Israel

Gershon Katz