Estimating proportions of objects from multispectral scanner data

Progress is reported in developing and testing methods of estimating, from multispectral scanner data, proportions of target classes in a scene when there are a significiant number of boundary pixels. Procedures were developed to exploit: (1) prior information concerning the number of object classes normally occurring in a pixel, and (2) spectral information extracted from signals of adjoining pixels. Two algorithms, LIMMIX and nine-point mixtures, are described along with supporting processing techniques. An important by-product of the procedures, in contrast to the previous method, is that they are often appropriate when the number of spectral bands is small. Preliminary tests on LANDSAT data sets, where target classes were (1) lakes and ponds, and (2) agricultural crops were encouraging

Hypercomplex quantum mechanics

The fundamental axioms of the quantum theory do not explicitly identify the algebraic structure of the linear space for which orthogonal subspaces correspond to the propositions (equivalence classes of physical questions). The projective geometry of the weakly modular orthocomplemented lattice of propositions may be imbedded in a complex Hilbert space; this is the structure which has traditionally been used. This paper reviews some work which has been devoted to generalizing the target space of this imbedding to Hilbert modules of a more general type. In particular, detailed discussion is given of the simplest generalization of the complex Hilbert space, that of the quaternion Hilbert module.Comment: Plain Tex, 11 page

Tau-crystallin/alpha-enolase: one gene encodes both an enzyme and a lens structural protein.

tau-Crystallin has been a major component of the cellular lenses of species throughout vertebrate evolution, from lamprey to birds. Immunofluorescence analysis of the embryonic turtle lens, using antiserum to lamprey tau-crystallin showed that the protein is expressed throughout embryogenesis and is present at high concentrations in all parts of the lens. Partial peptide sequence for the isolated turtle protein and deduced sequences for several lamprey peptides all revealed a close similarity to the glycolytic enzyme enolase (E.C. 4.2.1.11). A full-sized cDNA for putative duck tau-crystallin was obtained and sequenced, confirming the close relationship with alpha-enolase. Southern blot analysis showed that the duck genome contains a single alpha-enolase gene, while Northern blot analysis showed that the message for tau-crystallin/alpha-enolase is present in embryonic duck lens at 25 times the abundance found in liver. tau-Crystallin possesses enolase activity, but the activity is greatly reduced, probably because of age-related posttranslational modification. It thus appears that a highly conserved, important glycolytic enzyme has been used as a structural component of lens since the start of vertebrate evolution. Apparently the enzyme has not been recruited for its catalytic activity but for some distinct structural property. tau-Crystallin/alpha-enolase is an example of a multifunctional protein playing two very different roles in evolution but encoded by a single gene

Chemical Measurement and Fluctuation Scaling

Main abstract: Fluctuation scaling reports on all processes producing a data set. Some fluctuation scaling relationships, such as the Horwitz curve, follow exponential dispersion models which have useful properties. The mean-variance method applied to Poisson distributed data is a special case of these properties allowing the gain of a system to be measured. Here, a general method is described for investigating gain (G), dispersion (β), and process (α) in any system whose fluctuation scaling follows a simple exponential dispersion model, a segmented exponential dispersion model, or complex scaling following such a model locally. When gain and dispersion cannot be obtained directly, relative parameters, GR and βR, may be used. The method was demonstrated on data sets conforming to simple, segmented, and complex scaling. These included mass, fluorescence intensity, and absorbance measurements and specifications for classes of calibration weights. Changes in gain, dispersion, and process were observed in the scaling of these data sets in response to instrument parameters, photon fluxes, mathematical processing, and calibration weight class. The process parameter which limits the type of statistical process that can be invoked to explain a data set typically exhibited 04 possible. With two exceptions, calibration weight class definitions only affected β. Adjusting photomultiplier voltage while measuring fluorescence intensity changed all three parameters (0<α<0.8; 0<βR<3; 0<GR<4.1). The method provides a framework for calibrating and interpreting uncertainty in chemical measurement allowing robust compar ison of specific instruments, conditions, and methods. Supporting information abstract: On first inspection, fluctuation scaling data may appear to approximate a straight line when log transformed. The data presented in figure 5 of the main text gives a reasonable approximation to a straight line and for many purposes this would be sufficient. The purpose of the study of fluorescence intensity was to determine whether adjusting the voltage of a photomultiplier tube while measuring a fluorescent sample changes the process (α), the dispersion (β) and/or the gain (G). In this regard, the linear model established that PMT setting affects more than the gain. However, a detailed analysis beginning with testing for model mis-specification provides additional information. Specifically, Poisson behavior is only seen over a limited wavelength range in the 600 V and 700 V data sets

Concise review: An (Im)Penetrable Shield- How the Tumor Microenvironment Protects Cancer Stem Cells

Cancer stem cells (CSCs) are defined by their unlimited self-renewal ability and their capacity to initiate and maintain malignancy, traits that are not found in most cells that comprise the tumor. Although current cancer treatments successfully reduce tumor burden, the tumor will likely recur unless CSCs are effectively eradicated. This challenge is made greater by the protective impact of the tumor microenvironment (TME), consisting of infiltrating immune cells, endothelial cells, extracellular matrix, and signaling molecules. The TME acts as a therapeutic barrier through immunosuppressive, and thereby tumor-promoting, actions. These factors, outside of the cancer cell lineage, work in concert to shelter CSCs from both the body's intrinsic anticancer immunity and pharmaceutical interventions to maintain cancer growth. Emerging therapies aimed at the TME offer a promising new tool in breaking through this shield to target the CSCs, yet definitive treatments remain unrealized. In this review, we summarize the mechanisms by which CSCs are protected by the TME and current efforts to overcome these barrier