Elements of geometry: containing the first six books of Euclid, with a supplement on the quadrature of the circle, and the geometry of solids: to which are added, elements of plane and spherical trigonometry,

Mode of access: Internet.

Constructive geometry of plane curves, with numerous examples,

Mode of access: Internet.

Contributions to the geometry of the triangle,

Mode of access: Internet.

The elementary differential geometry of plane curves,

Mode of access: Internet.

On the Geometry of Rectifiable Sets with Carleson and Poincare-type inequlaities

Thesis (Ph.D.)--University of Washington, 2016-06

Gravity spun polycaprolactone fibers for applications in vascular tissue engineering:proliferation and function of human vascular endothelial cells

Poly(ε-caprolactone) (PCL) fibers produced by wet spinning from solutions in acetone under low-shear (gravity-flow) conditions resulted in fiber strength of 8 MPa and stiffness of 0.08 Gpa. Cold drawing to an extension of 500% resulted in an increase in fiber strength to 43 MPa and stiffness to 0.3 GPa. The growth rate of human umbilical vein endothelial cells (HUVECs) (seeded at a density of 5 × 104 cells/mL) on as-spun fibers was consistently lower than that measured on tissue culture plastic (TCP) beyond day 2. Cell proliferation was similar on gelatin-coated fibers and TCP over 7 days and higher by a factor of 1.9 on 500% cold-drawn PCL fibers relative to TCP up to 4 days. Cell growth on PCL fibers exceeded that on Dacron monofilament by at least a factor of 3.7 at 9 days. Scanning electron microscopy revealed formation of a cell layer on samples of cold-drawn and gelatin-coated fibers after 24 hours in culture. Similar levels of ICAM-1 expression by HUVECs attached to PCL fibers and TCP were measured using RT-PCR and flow cytometry, indicative of low levels of immune activation. Retention of a specific function of HUVECs attached to PCL fibers was demonstrated by measuring their immune response to lipopolysaccharide. Levels of ICAM-1 expression increased by approximately 11% in cells attached to PCL fibers and TCP. The high fiber compliance, favorable endothelial cell proliferation rates, and retention of an important immune response of attached HUVECS support the use of gravity spun PCL fibers for three-dimensional scaffold production in vascular tissue engineering. © Mary Ann Liebert, Inc.

Generalization of a Conjecture in the Geometry of Polynomials

In this paper we survey work on and around the following conjecture, which was first stated about 45 years ago: If all the zeros of an algebraic polynomial p (of degree n ≥ 2) lie in a disk with radius r, then, for each zero z1 of p, the disk with center z1 and radius r contains at least one zero of the derivative p′ . Until now, this conjecture has been proved for n ≤ 8 only. We also put the conjecture in a more general framework involving higher order derivatives and sets defined by the zeros of the polynomials.

Fuzzy sets: Abstraction Axiom, Statistical Interpretation, Observations of Fuzzy Sets

The issues relating fuzzy sets definition are under consideration including the analogue for separation axiom, statistical interpretation and membership function representation by the conditional Probabilities.

Geometry of Warped Product Semi-Invariant Submanifolds of a Locally Riemannian Product Manifold

2000 Mathematics Subject Classification: 53C42, 53C15.

Geometry of Dirac Operators

Let $M$ be a compact, oriented, even dimensional Riemannian manifold and let $S$ be a Clifford bundle over $M$ with Dirac operator $D$. Then \[ \textsc{Atiyah Singer: } \quad \text{Ind } \mathsf{D}= \int_M \hat{\mathcal{A}}(TM)\wedge \text{ch}(\mathcal{V}) \] where $\mathcal{V} =\text{Hom}_{\mathbb{C}l(TM)}(\slashed{\mathsf{S}},S)$. We prove the above statement with the means of the heat kernel of the heat semigroup $e^{-tD^2}$. The first outstanding result is the McKean-Singer theorem that describes the index in terms of the supertrace of the heat kernel. The trace of heat kernel is obtained from local geometric information. Moreover, if we use the asymptotic expansion of the kernel we will see that in the computation of the index only one term matters. The Berezin formula tells us that the supertrace is nothing but the coefficient of the Clifford top part, and at the end, Getzler calculus enables us to find the integral of these top parts in terms of characteristic classes.

Influence of the cutting edge micro-geometry of PCBN tools on the flank wear in orthogonal quenched and tempered turning M2 steel

Quenched and tempered high-speed steels obtained by powder metallurgy are commonly used in automotive components, such as valve seats of combustion engines. In order to machine these components, tools with high wear resistance and appropriate cutting edge geometry are required. This work aims to investigate the influence of the edge preparation of polycrystalline cubic boron nitride (PCBN) tools on the wear behavior in the orthogonal longitudinal turning of quenched and tempered M2 high-speed steels obtained by powder metallurgy. For this research, PCBN tools with high and low-CBN content have been used. Two different cutting edge geometries with a honed radius were tested: with a ground land (S shape) and without it (E shape). Also, the cutting speed was varied from 100 to 220 m/min. A rigid CNC lathe was used. The results showed that the high-CBN, E-shaped tool presented the longest life for a cutting speed of 100 m/min. High-CBN tools with a ground land and honed edge radius (S shaped) showed edge damage and lower values of the tool’s life. Low-CBN, S-shaped tools showed similar results, but with an inferior performance when compared with tools with high CBN content in both forms of edge preparation.

Withaferin A promotes proliferation and migration of brain endothelial cells

Purpose: To investigate the effect of withaferin A (WFA) on the proliferation and migration of brain endothelial cells. Methods: BALB-5023 mouse microvascular cells were treated with a range of withaferin A (WFA) concentrations from 10 to 100 ng/mL. Dojindo’s CCK-8 cell proliferation kit was used for the analysis of cell proliferation. Transwell cell culture inserts were used to determine the migration potential of WFAtreated endothelial cells. Absorbance was measured at 450 nm on an enzyme-linked immunosorbent (ELISA) reader. Results: The results revealed a significant increase in the proliferation and migration of endothelial cells following treatment with a low concentration (30 ng/mL) of WFA compared with the higher concentration (> 10 ng/mL). The effect was further enhanced when WFA was used in combination with soluble Fas ligand (sFasL). Autocrine signaling of vascular endothelial growth factor (VEGF) by endothelial cells was significantly increased following treatment with WFA or in combination with sFasL. WFA increased the expression of Fas on endothelial cells, suggesting the involvement of sFasL in the proliferation and migration of brain endothelial cells. Conclusion: Thus, WFA promotes the proliferation and migration of endothelial cells through increase in the expression of Fas and secretion of VEGF.

Information Fusion and Hierarchical Knowledge Discovery by ARTMAP Neural Networks

Mapping novel terrain from sparse, complex data often requires the resolution of conflicting information from sensors working at different times, locations, and scales, and from experts with different goals and situations. Information fusion methods help resolve inconsistencies in order to distinguish correct from incorrect answers, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods developed here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an objects class is car, vehicle, or man-made. Underlying relationships among objects are assumed to be unknown to the automated system of the human user. The ARTMAP information fusion system uses distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierarchial knowledge structures. The system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships. The procedure is illustrated with two image examples.

Self-Organizing Hierarchical Knowledge Discovery by an ARTMAP Image Fusion System

Classifying novel terrain or objects front sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods described here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among objects are assumed to be unknown to the automated system or the human user. The ARTMAP information fusion system used distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierarchical knowledge structures. The system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships.

Self-Organizing Information Fusion and Hierarchical Knowledge Discovery: A New Framework Using Artmap Neural Networks

Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors woring at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when eveidence variously suggests that and object's class is car, truck, or airplane. The methods described her address a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among classes are assumed to be unknown to the autonomated system or the human user. The ARTMAP information fusion system uses distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierachical knowlege structures. The fusion system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships. The procedure is illustrated with two image examples, but is not limited to image domain.