Spatial Association from the Perspective of Mutual Information

Measures of spatial association are important to reveal the spatial structures and patterns in geographical phenomena. They have utility for spatial interpolation, stochastic simulation, and causal inference, among others. Such measures are abundantly available for continuous spatial variables, whereas for categorical spatial variables they are less well developed. In this research, we developed a measure of spatial association for categorical spatial variables coined the entropogram, quantifying its spatial association using mutual information. Mutual information concerns information shared by pairs of random variables at different locations as revealed by their observed joint frequency distribution and marginal frequency distributions. The developed new measure is modeled as a function of lag in analogy to the variogram. Whereas existing measures focus mainly on interstate relationships, the entropogram models the spatial correlation in categorical spatial variables holistically. In this way, the entropogram imparts multiple advantages, for example, simplifying the representation of spatial structure for categorical variables and facilitating communication. The entropogram also reflects variation in the spatial correlation between different states. We first explored the properties of the entropogram in a simulation study. Then, we applied the entropogram to analyze the spatial association of land cover types in Qinxian, Shanxi, China. We conclude that the entropogram provides a suitable addition to existing measures of spatial association for applications in a wide range of disciplines where the categorical spatial variable is of interest.</p

Equations for filling factor estimation in opal matrix

We consider two equations for the filling factor estimation of infiltrated zinc oxide (ZnO) in silica (SiO_2) opal and gallium nitride in ZnO opal. The first equation is based on the effective medium approximation, while the second one - on Maxwell-Garnett approximation. The comparison between two filling factors shows that both equations can be equally used for the estimation of the quantity of infiltrated nanocrystals inside opal matrix.Comment: 14 pages, 7 figures, 1 table. Addendum to the article: http://arxiv.org/abs/physics/050815

One‐Shot Active Learning for Globally Optimal Battery Electrolyte Conductivity**

Non-aqueous aprotic battery electrolytes need to perform well over a wide range of temperatures in practical applications. Herein we present a one-shot active learning study to find all conductivity optima, confidence bounds, and relating formulation trends in the temperature range from −30 °C to 60 °C. This optimization is enabled by a high-throughput formulation and characterization setup guided by one-shot active learning utilizing robust and heavily regularized polynomial regression. Whilst there is an initially good agreement for intermediate and low temperatures, there is a need for the active learning step to improve the model for high temperatures. Optimized electrolyte formulations likely correspond to the highest physically possible conductivities within this formulation system when compared to literature data. A thorough error propagation analysis yields a fidelity assessment of conductivity measurements and electrolyte formulation

4-Aminopyridine Decreases Progesterone Production by Porcine Granulosa Cells

BACKGROUND: Ion channels occur as large families of related genes with cell-specific expression patterns. Granulosa cells have been shown to express voltage-gated potassium channels from more than one family. The purpose of this study was to determine the effects of 4-aminopyridine (4-AP), an antagonist of KCNA but not KCNQ channels. METHODS: Granulosa cells were isolated from pig follicles and cultured with 4-AP, alone or in combination with FSH, 8-CPT-cAMP, estradiol 17β, and DIDS. Complimentary experiments determined the effects of 4-AP on the spontaneously established pig granulosa cell line PGC-2. Granulosa cell or PGC-2 function was assessed by radio-immunoassay of media progesterone accumulation. Cell viability was assessed by trypan blue exclusion. Drug-induced changes in cell membrane potential and intracellular potassium concentration were documented by spectrophotometric determination of DiBAC(4)(3) and PBFI fluorescence, respectively. Expression of proliferating cell nuclear antigen (PCNA) and steroidogenic acute regulatory protein (StAR) was assessed by immunoblotting. Flow cytometry was also used to examine granulosa cell viability and size. RESULTS: 4-AP (2 mM) decreased progesterone accumulation in the media of serum-supplemented and serum-free granulosa cultures, but inhibited cell proliferation only under serum-free conditions. 4-AP decreased the expression of StAR, the production of cAMP and the synthesis of estradiol by PGC-2. Addition of either 8-CPT-cAMP or estradiol 17β to serum-supplemented primary cultures reduced the inhibitory effects of 4-AP. 4-AP treatment was also associated with increased cell size, increased intracellular potassium concentration, and hyperpolarization of resting membrane potential. The drug-induced hyperpolarization of resting membrane potential was prevented either by decreasing extracellular chloride or by adding DIDS to the media. DIDS also prevented 4-AP inhibition of progesterone production. CONCLUSION: 4-AP inhibits basal and FSH-stimulated progesterone production by pig granulosa cells via drug action at multiple interacting steps in the steroidogenic pathway. These inhibitory effects of 4-AP on steroidogenesis may reflect drug-induced changes in intracellular concentrations of K(+)and Cl(- )as well as granulosa cell resting membrane potential

Algorithm and performance of a clinical IMRT beam-angle optimization system

This paper describes the algorithm and examines the performance of an IMRT beam-angle optimization (BAO) system. In this algorithm successive sets of beam angles are selected from a set of predefined directions using a fast simulated annealing (FSA) algorithm. An IMRT beam-profile optimization is performed on each generated set of beams. The IMRT optimization is accelerated by using a fast dose calculation method that utilizes a precomputed dose kernel. A compact kernel is constructed for each of the predefined beams prior to starting the FSA algorithm. The IMRT optimizations during the BAO are then performed using these kernels in a fast dose calculation engine. This technique allows the IMRT optimization to be performed more than two orders of magnitude faster than a similar optimization that uses a convolution dose calculation engine.Comment: Final version that appeared in Phys. Med. Biol. 48 (2003) 3191-3212. Original EPS figures have been converted to PNG files due to size limi