Diversity of Lecidea (Lecideaceae, Ascomycota) species revealed by molecular data and morphological characters

The diversity of lichens, especially crustose species, in continental Antarctica is still poorly known. To overcome difficulties with the morphology based species delimitations in these groups, we employed molecular data (nuclear ITS and mitochondrial SSU rDNA sequences) to test species boundaries within the genus Lecidea. Sampling was done along a north–south transect at five different areas in the Ross Sea region (Cape Hallett, Botany Bay to Mount Suess, Taylor Valley, Darwin Area and Mount Kyffin). A total of 153 specimens were collected from 13 localities. Phylogenetic analyses also include specimens from other regions in Antarctica and non-Antarctic areas. Maximum parsimony, maximum likelihood and Bayesian analyses agreed in placing the samples from continental Antarctica into four major groups. Based on this phylogenetic estimate, we restudied the micromorphology and secondary chemistry of these four clades to evaluate the use of these characters as phylogenetic discriminators. These clades are identified as the following species Lecidea cancriformis, L. andersonii as well as the new species L. polypycnidophora Ruprecht & Türk sp. nov. and another previously unnamed clade of uncertain status, referred to as Lecidea sp. (L. UCR1)

Cost Drivers of Operation Charges and Variation over Time: An Analysis Based on Semiparametric SUR Models

Although building operating charges have turned out to be a major determinant of profitability for real estate investments, there is a noticeable lack of reports or studies that analyze these costs with state-of-the-art statistical techniques. Specifically, past studies usually assume linear relationships between costs and building attributes, they do not control for cluster-specific or longitudinal effects and do not account for the simultaneous structure of cost categories. Therefore, in this study we provide a novel approach to real estate cost benchmarking: We analyze the effects of building attributes on electricity, heating and maintenance costs for office buildings in Germany in a multivariate structured additive regression (STAR) model simultaneously, modeling potentially nonlinear effects as P(enalized)-Splines and controlling for cluster-specific and individual heterogeneity in a three-way random effects structure. This way, we gain insights into how building attributes influence costs, and how cost levels vary across cities, companies and buildings. We furthermore derive quality-adjusted time indices for the two major German submarkets, the former German Democratic Republic and the old West German states. The results obtained can be used to derive portfolio allocation strategies and for planning, constructing, operating and redeveloping real estate

Історико-методологічна конкуренція етноцентризму та антропоцентризму в євроінтеграції України

Статтю присвячено актуальній проблемі гуманістичної трансформації методологічних підстав критичного мислення у дослідженні та викладанні історії. Наголошується на ключовій ролі ідеї свободи у теоретико-методологічному дискурсі. На прикладі конфлікту інтерпретацій, акцентується потреба розвитку навичок самостійного аналізу історичних фактів і процесів як найважливішої передумови продуктивного соціального діалогу й гарантії особистої свободи громадянина.Статья посвящена актуальной проблеме гуманистической трансформации методологических оснований критического мышления в изучении и преподавании истории. Подчеркивается ключевая роль идеи свободы в теоретико-методологическом дискурсе. На примере объективной оценки существующего конфликта интерпретаций, акцентируется потребность развития навыков самостоятельного анализа исторических фактов и процессов как важнейшей предпосылки продуктивного социального диалога и гарантии личной свободы гражданина.The article deals with the problem of humanistic transformation of critical thinking methodology in history (teaching and learning aspects).The key-role of the idea of freedom in theoretic and methodological discourse is being underlined.The example to evaluate objectively the existing conflict of interpretations helps to accentuate the necessity of developing the skills to analyse historical facts and processes as an important precondition for effective social dialogue and private civil freedom guarantees

Why GPS makes distances bigger than they are

Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS), are among the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation error. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS: the distance between two points recorded with a GPS is -- on average -- bigger than the true distance between these points. This systematic `overestimation of distance' becomes relevant if the influence of interpolation error can be neglected, which is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and we illustrate that it functionally depends on the autocorrelation of GPS measurement error ($C$). We argue that $C$ can be interpreted as a quality measure for movement data recorded with a GPS. If there is strong autocorrelation any two consecutive position estimates have very similar error. This error cancels out when average speed, distance or direction are calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine $C$ in real-world GPS movement data sampled at high frequencies. We apply our approach to a set of pedestrian and a set of car trajectories. We find that the measurement error in the data is strongly spatially and temporally autocorrelated and give a quality estimate of the data. Finally, we want to emphasize that all our findings are not limited to GPS alone. The systematic bias and all its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected.Comment: 17 pages, 8 figures, submitted to IJGI

Modeling House Prices using Multilevel Structured Additive Regression

This paper analyzes house price data belonging to three hierarchical levels of spatial units. House selling prices with associated individual attributes (the elementary level-1) are grouped within municipalities (level-2), which form districts (level-3), which are themselves nested in counties (level-4). Additionally to individual attributes, explanatory covariates with possibly nonlinear effects are available on two of these spatial resolutions. We apply a multilevel version of structured additive regression (STAR) models to regress house prices on individual attributes and locational neighborhood characteristics in a four level hierarchical model. In multilevel STAR models the regression coefficients of a particular nonlinear term may themselves obey a regression model with structured additive predictor. The framework thus allows to incorporate nonlinear covariate effects and time trends, smooth spatial effects and complex interactions at every level of the hierarchy of the multilevel model. Moreover we are able to decompose the spatial heterogeneity effect and investigate its magnitude at different spatial resolutions allowing for improved predictive quality even in the case of unobserved spatial units. Statistical inference is fully Bayesian and based on highly efficient Markov chain Monte Carlo simulation techniques that take advantage of the hierarchical structure in the data

Phase Transitions and Adsorption Isotherm in Multilayer Adsorbates with Lateral Interactions

We analyze here a model for an adsorbate system composed of many layers by extending a theoretical approach used to describe pattern formation on a monolayer of adsorbates with lateral interactions. The approach shows, in addition to a first order phase transition in the first layer, a transition in the second layer together with evidence of a "cascade" of transitions if more layers are included. The transition profiles, showing a staircase structure, corroborate this picture. The adsorption isotherm that came out of this approach is in qualitative agreement with numerical and experimental results.Comment: Submited to Physica A, LaTex, 22 pgs, 6 figure

Estimating specific surface area of fine stream bed sediments from geochemistry

Specific surface area (SSA) of headwater stream bed sediments is a fundamental property which determines the nature of sediment surface reactions and influences ecosystem-level, biological processes. Measurements of SSA – commonly undertaken by BET nitrogen adsorption – are relatively costly in terms of instrumentation and operator time. A novel approach is presented for estimating fine (2.5 mg kg−1), four elements were identified as significant predictors of SSA (ordered by decreasing predictive power): V > Ca > Al > Rb. The optimum model from these four elements accounted for 73% of the variation in bed sediment SSA (range 6–46 m2 g−1) with a root mean squared error of prediction – based on leave-one-out cross-validation – of 6.3 m2 g−1. It is believed that V is the most significant predictor because its concentration is strongly correlated both with the quantity of Fe-oxides and clay minerals in the stream bed sediments, which dominate sediment SSA. Sample heterogeneity in SSA – based on triplicate measurements of sub-samples – was a substantial source of variation (standard error = 2.2 m2 g−1) which cannot be accounted for in the regression model. The model was used to estimate bed sediment SSA at the other 1792 sites and at 30 duplicate sites where an extra sediment sample had been collected, 25 m from the original site. By delineating sub-catchments for the headwater sediment sites only those sub-catchments were selected with a dominant (>50% of the sub-catchment area) bedrock formation and land use type; the bedrock and land use classes accounted for 39% and 7% of the variation in bed sediment SSA, respectively. Variation in estimated, fine bed sediment SSA from the paired, duplicate sediment sites was small (2.7 m2 g−1), showing that local variation in SSA at stream sites is modest when compared to that between catchments. How the approach might be applied in other environments and its potential limitations are discussed

Statistical risk analysis for real estate collateral valuation using Bayesian distributional and quantile regression

The Basel II framework strictly defines the conditions under which financial institutions are authorized to accept real estate as collateral in order to decrease their credit risk. A widely used concept for its valuation is the hedonic approach. It assumes, that a property can be characterized by a bundle of covariates that involves both individual attributes of the building itself and locational attributes of the region where the building is located in. Each of these attributes can be assigned an implicit price, summing up to the value of the entire property. With respect to value-at-risk concepts financial institutions are often not only interested in the expected value but also in different quantiles of the distribution of real estate prices. To meet these requirements, we develop and compare multilevel structured additive regression models based on GAMLSS type approaches and quantile regression, respectively. Our models involve linear, nonlinear and spatial effects. Nonlinear effects are modeled with P-splines, spatial effects are represented by Gaussian Markov random fields. Due to the high complexity of the models statistical inference is fully Bayesian and based on highly efficient Markov chain Monte Carlo simulation techniques

Fulminant systemic capillary leak syndrome due to C1 inhibitor deficiency complicating acute dermatomyositis: a case report

INTRODUCTION: Dermatomyositis is a chronic inflammatory disorder characterized by muscular and dermatologic symptoms with variable internal organ involvement. This is the first report on a patient with acute dermatomyositis and fulminant systemic capillary leak syndrome. CASE PRESENTATION: A 69-year-old Caucasian woman with chronic dermatomyositis presented with clinical signs of severe hypovolemic shock and pronounced hemoconcentration (hematocrit, 69%). Her colloid osmotic pressure was 4.6mmHg. Following a bolus dose of prednisolone (500mg), fluid resuscitation was initiated. During volume loading, anasarca and acute respiratory distress rapidly developed. Echocardiography revealed an underfilled, hypokinetic, diastolic dysfunctional left ventricle with pericardial effusion but no signs of tamponade. Despite continued fluid resuscitation and high-dosed catecholamine therapy, the patient died from refractory shock 12 hours after intensive care unit admission. A laboratory analysis of her complement system suggested the presence of C1 inhibitor deficiency as the cause for systemic capillary leakage. The post-mortem examination revealed bilateral pleural, pericardial and peritoneal effusions as well as left ventricular hypertrophy with patchy myocardial fibrosis. Different patterns of endomysial/perimysial lymphocytic infiltrations adjacent to degenerated cardiomyocytes in her myocardium and necrotic muscle fibers in her right psoas major muscle were found in the histological examination. CONCLUSIONS: This case report indicates that acute exacerbation of chronic dermatomyositis can result in a fulminant systemic capillary leak syndrome with intense hemoconcentration, hypovolemic shock and acute heart failure. In the presented patient, the cause for diffuse capillary leakage was most probably acquired angioedema, a condition that has been associated with both lymphoproliferative and autoimmunologic disorders

Re-thinking resuscitation: Leaving blood pressure cosmetics behind and moving forward to permissive hypotension and a tissue perfusion-based approach

Definitions of shock and resuscitation endpoints traditionally focus on blood pressures and cardiac output. This carries a high risk of overemphasizing systemic hemodynamics at the cost of tissue perfusion. In line with novel shock definitions and evidence of the lack of a correlation between macro- and microcirculation in shock, we recommend that macrocirculatory resuscitation endpoints, particularly arterial and central venous pressure as well as cardiac output, be reconsidered. In this viewpoint article, we propose a three-step approach of resuscitation endpoints in shock of all origins. This approach targets only a minimum individual and context-sensitive mean arterial blood pressure (for example, 45 to 50 mm Hg) to preserve heart and brain perfusion. Further resuscitation is exclusively guided by endpoints of tissue perfusion irrespectively of the presence of arterial hypotension ('permissive hypotension'). Finally, optimization of individual tissue (for example, renal) perfusion is targeted. Prospective clinical studies are necessary to confirm the postulated benefits of targeting these resuscitation endpoints