Remote sensing of phytoplankton pigments: A comparison of empirical and theoretical approaches

Algorithms that have been used on a routine basis for remote sensing of the phytoplankton pigment, chlorophyll- a, from ocean colour data from satellite sensors such as the CZCS (Coastal Zone Color Scanner), SeaWiFS (Sea Viewing Wide Field-of-View Sensor) and OCTS (Ocean Colour and Temperature Scanner) are all of an empirical nature. However, there exist theoretical models that allow ocean colour to be expressed as a function of the inherent optical properties of seawater, such as the absorption coefficient and the backscattering coefficient. These properties can in turn be expressed as functions of chlorophyll- a, at least for the so-called Case 1 waters in which phytoplankton may be considered to be the single, independent variable responsible for most of the variations in the marine optical properties. Here, we use such a theoretical approach to model variations in ocean colour as a function of chlorophyll- a concentration, and compare the results with some empirical models in routine use. The parameters of phytoplankton absorption necessary for the implementation of the ocean colour model are derived from our database of over 700 observations of phytoplankton absorption spectra and concurrent measurements of phytoplankton pigments by HPLC (High Performance Liquid Chromatography) techniques. Since there are reports in the literature that significant differences exist in the performance of the algorithms in polar regions compared with lower latitudes, the model is first implemented using observations made at latitudes less than 50. It is then applied to the Labrador Sea, a high-latitude environment. Our results show that there are indeed differences in the performance of the algorithm at high latitudes, and that these differences may be attributed to changes in the optical characteristics of phytoplankton that accompany changes in the taxonomic composition of their assemblages. The sensitivities of the model to assumptions made regarding absorption by coloured dissolved organic matter (or yellow substances) and backscattering by particles are examined. The importance of Raman scattering on ocean colour and its influence on the algorithms are also investigated.     

On-Line Learning of Rectangles and Unions of Rectangles

Machine Learning - We design efficient algorithms for on-line learning of axis-parallel rectangles (and for the union of two such rectangles) in the common model for on-line learning with...     

Progesterone in the uterus. VI. On the question of the in vitro progesterone metabolism in human endometrium and myometrium

Human endometrial and myometrial tissue pieces were incubated with radioactively labeled progesterone in nutrient medium for 20 min., 1 hr and 2 hrs. The only compound extracted from the tissue pieces and the nutrient fluids was identified to be progesterone by TLC, chemical reactions and crystallization experiments. Radiometabolites could not be detected in the tissue pieces and in the nutrient fluids under the experimental conditions applied (10(-7) M 1,2-3H-progesterone in the incubation medium). This result is comparable with recent findings on the in vitro progesterone metabolism by rat uterine tissue.     

Relating dietary diversity and food variety scores to vegetable production and socio-economic status of women in rural Tanzania

The objective of the present study was to measure diversity in nutrition with dietary scores, and to assess their relationship to vegetable production and the socio-economic status of women in rural Tanzania. A dietary diversity score (DDS) and a food variety score (FVS) were created from data gathered with three semi-quantitative 24-h recalls performed during three non-consecutive seasons during 2006/2007. Data on vegetable production, selling and buying and socio-economic data was gathered with a semi-quantitative questionnaire. A total of 252 randomly selected women from three districts of north-eastern and central Tanzania participated. The median DDS of 6 and the mean FVS of 8.3 were low, suggesting an overall poor dietary quality, with about one third of participants having an alarmingly low DDS of only two to four food groups per day. These women consumed a very basic diet consisting mainly of cereals and vegetables. Differences among districts were pronounced while those among seasons were less distinct. The DDS and FVS were both significantly associated with ethnicity, occupation and status within the household of participants. As a more varied diet is not necessarily healthier, integration of both quantity and quality in the scores is proposed for future studies. This can be achieved, for example, by weighing food types according to their importance in the diet. As both scores are linked to the production, selling and buying of vegetables, the promotion of homestead food production may be a good way to improve dietary diversity.     

Magnification of label maps with a topology-preserving level-set method

Image segmentation aims at partitioning an image into multiple segments. The application of this procedure produces a label map (also referred to as segmentation map) that classifies the pixels of the original image. In contrast to "natural" images, label maps are nominal-scale images, typically represented as integer-valued images. Nominal-scaled label maps can also appear as a representation of the raw data in areas, such as in geostatistics. In some applications, the original resolution of a label map does not suffice and a larger size map has to be generated. In this paper, we present a magnification algorithm for label maps and nominal images. The main property of our method is that it preserves the topology during the magnification process, which means that no isolated pixel vanishes. To the best of our knowledge, apart from nearest-neighbor interpolation, the problem of label map magnification has not previously been addressed in the literature. The main idea of the proposed method is to accomplish a boundary refinement by smoothing the regions' boundaries on a finer grid. The method relies on well known methods, namely, the fundamental operations of morphological image processing-erosion and dilation-and the level-set method. The level-set method is well suited for our purposes since it does not depend on a parametrization and it is numerically stable. The topological flexibility of the level-set method-often found to be an advantage in applications-is a drawback here, since the topology of the original label map should be preserved. However, using the so-called simple point criterion from digital topology, one can adapt the conventional level-set method so that the topology will not be modified throughout the magnification procedure.     

Tuning Molecular Self‐Assembly on Bulk Insulator Surfaces by Anchoring of the Organic Building Blocks

Molecular self‐assembly constitutes a versatile strategy for creating functional structures on surfaces. Tuning the subtle balance between intermolecular and molecule‐surface interactions allows structure formation to be tailored at the single‐molecule level. While metal surfaces usually exhibit interaction strengths in an energy range that favors molecular self‐assembly, dielectric surfaces having low surface energies often lack sufficient interactions with adsorbed molecules. As a consequence, application‐relevant, bulk insulating materials pose significant challenges when considering them as supporting substrates for molecular self‐assembly. Here, the current status of molecular self‐assembly on surfaces of wide‐bandgap dielectric crystals, investigated under ultrahigh vacuum conditions at room temperature, is reviewed. To address the major issues currently limiting the applicability of molecular self‐assembly principles in the case of dielectric surfaces, a systematic discussion of general strategies is provided for anchoring organic molecules to bulk insulating materials.