Ultramicroscopic studies on the human corpus luteum menstruationis and graviditatis

In high active steroid producing cells of the human corpus luteum we can find in the cytoplasm a well developed smooth endoplasmic reticulum in form of smooth tubules and homogenously spread vesicles resulting from an active metabolic process. We also find specific concertinalike folded membrane complexes which too belong to the endoplasmic reticulum. Numerous mainly tubular mitochondria contain dense lipoid inclusions. Their close conection with the endoplasmic vesicles is expression of a direct interaction of both cell organelles in progesterone production. The transport of the intracellular formed steroid hormones to the capillary takes place via locally enlarged intercellular spaces which communicate with the pericapillary space. On the other hand there are pericellular canaliculi which are coated with a membrane. They have no direct connection to the pericapillar space.     

Measuring structural similarity of semistructured data based on information-theoretic approaches

We propose and experimentally evaluate different approaches for measuring the structural similarity of semistructured documents based on information-theoretic concepts. Common to all approaches is a two-step procedure: first, we extract and linearize the structural information from documents, and then, we use similarity measures that are based on, respectively, Kolmogorov complexity and Shannon entropy to determine the distance between the documents. Compared to other approaches, we are able to achieve a linear run-time complexity and demonstrate in an experimental evaluation that the results of our technique in terms of clustering quality are on a par with or even better than those of other, slower approaches.     

Relationships of low serum vitamin D<Subscript>3</Subscript>with anthropometry and markers of the metabolic syndrome and diabetes in overweight and obesity

Low serum 25 hydroxyvitamin D₃ (vitamin D₃) is known to perturb cellular function in many tissues, including the endocrine pancreas, which are involved in obesity and type II diabetes mellitus (TIIDM). Vitamin D₃ insufficiency has been linked to obesity, whether obesity is assessed by body mass index (BMI) or waist circumference (waist). Central obesity, using waist as the surrogate, is associated with the metabolic syndrome (MetSyn), insulin resistance, TIIDM and atherosclerotic cardiovascular disease (CVD). We tested how vitamin D₃ was related to measures of fat mass, MetSyn markers, haemoglobin A_1c (HbA_1c) and MetSyn in a cross-sectional sample of 250 overweight and obese adults of different ethnicities. There were modest inverse associations of vitamin D₃ with body weight (weight) (r = -0.21, p = 0.0009), BMI (r = -0.18, p = 0.005), waist (r = -0.14, p = 0.03), [but not body fat % (r = -0.08, p = 0.24)], and HbA_1c (r = -0.16, p = 0.01). Multivariable regression carried out separately for BMI and waist showed a decrease of 0.74 nmol/L (p = 0.002) in vitamin D₃ per 1 kg/m² increase in BMI and a decrease of 0.29 nmol/L (p = 0.01) per 1 cm increase in waist, with each explaining approximately 3% of the variation in vitamin D₃ over and above gender, age, ethnicity and season.     

Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information

A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, we developed models relating field-measured response variables to plot attributes serving as the predictor variables. The plot attributes came from intersecting plot coordinates with geospatial datasets. Consequently, these models serve as mapping models. The geospatial predictor variables included Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; land cover proportions and other data from the National Land Cover Dataset (NLCD); topographic variables; monthly and annual climate parameters; and other ancillary variables. We segmented the mapping models for the U.S. into 65 ecologically similar mapping zones, plus Alaska and Puerto Rico. First, we developed a forest mask by modeling the forest vs. nonforest assignment of field plots as functions of the predictor layers using classification trees in See5©. Secondly, forest biomass models were built within the predicted forest areas using tree-based algorithms in Cubist©. To validate the models, we compared field-measured with model-predicted forest/nonforest classification and biomass from an independent test set, randomly selected from available plot data for each mapping zone. The estimated proportion of correctly classified pixels for the forest mask ranged from 0.79 in Puerto Rico to 0.94 in Alaska. For biomass, model correlation coefficients ranged from a high of 0.73 in the Pacific Northwest, to a low of 0.31 in the Southern region. There was a tendency in all regions for these models to over-predict areas of small biomass and under-predict areas of large biomass, not capturing the full range in variability. Map-based estimates of forest area and forest biomass compared well with traditional plot-based estimates for individual states and for four scales of spatial aggregation. Variable importance analyses revealed that MODIS-derived information could contribute more predictive power than other classes of information when used in isolation. However, the true contribution of each variable is confounded by high correlations. Consequently, excluding any one class of variables resulted in only small effects on overall map accuracy. An estimate of total C pools in live forest biomass of U.S. forests, derived from the nationwide biomass map, also compared well with previously published estimates.     

Investigation of heat transfer and pressure drop of CO2 two-phase flow in a horizontal minichannel

An innovative cooling system based on evaporative CO₂ two-phase flow is under investigation for the tracker detectors upgrade at CERN (European Organization for Nuclear Research). The radiation hardness and the excellent thermodynamic properties emphasize carbon dioxide as a cooling agent in the foreseen minichannels. A circular stainless steel tube in horizontal orientation with an inner diameter of 1.42 mm and a length of 0.3 m has been used as a test section to perform the step-wise scanning of the vapor quality in the entire two-phase region. To characterize the heat transfer and the pressure drop depending on the vapor quality in the tube, measurements have been performed by varying the mass flux from 300 to 600 kg/m² s, the heat flux from 7.5 to 29.8 kW/m² and the saturation temperature from ?40 to 0 °C (reduced pressures from 0.136 to 0.472). Heat transfer coefficients between 4 kW/m² K and 28 kW/m² K and pressure gradients up to 75 kPa/m were registered. The measured data was analyzed corresponding to the dependencies on heat flux, mass flux and saturation temperature. A database has been established containing about 2000 measurement points. The experimental data was compared with common models recently developed by Cheng et al. [1], [2] to cross check their applicability. The overall trends and experimental data were reproduced as predicted by the models before the dryout onset, and deviations have been analyzed. A modified friction factor for the pressure drop model [1] in mist flow has been proposed based on the experimental data.