Geodesics of Surface of Revolution
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Engineering Curves – I
Engineering Curves – I 1. Classification 2. Conic sections - explanation 3. Common Definition 4. Ellipse – ( six methods of construction) 5. Parabola – ( Three methods of construction) 6. Hyperbola – ( Three methods of construction ) 7. Methods of drawing Tangents & Normals ( four cases) Engineering Curves – II 1. Classification 2. Definitions 3. Involutes - (five cases) 4. Cycloid 5. Trochoids – (Superior and Inferior) 6. Epic cycloid and Hypo - cycloid 7. Spiral (Two cases) 8. Helix – on cylinder & on cone 9. Methods of drawing Tangents and Normals (Three cases) ENGINEERING CURVES Part- I {Conic Sections} ELLIPSE PARABOLA HYPERBOLA 1.Concentric Circle Method 1.Rectangle Method 1.Rectangular Hyperbola (coordinates given) 2.Rectangle Method 2 Method of Tangents ( Triangle Method) 2 Rectangular Hyperbola 3.Oblong Method (P-V diagram - Equation given) 3.Basic Locus Method 4.Arcs of Circle Method (Directrix – focus) 3.Basic Locus Method (Directrix – focus) 5.Rhombus Metho 6.Basic Locus Method Methods of Drawing (Directrix – focus) Tangents & Normals To These Curves. CONIC SECTIONS ELLIPSE, PARABOLA AND HYPERBOLA ARE CALLED CONIC SECTIONS BECAUSE THESE CURVES APPEAR ON THE SURFACE OF A CONE WHEN IT IS CUT BY SOME TYPICAL CUTTING PLANES. OBSERVE ILLUSTRATIONS GIVEN BELOW.. Ellipse Section Plane Section Plane Hyperbola Through Generators Parallel to Axis. Section Plane Parallel to end generator. COMMON DEFINATION OF ELLIPSE, PARABOLA & HYPERBOLA: These are the loci of points moving in a plane such that the ratio of it’s distances from a fixed point And a fixed line always remains constant. The Ratio is called ECCENTRICITY. (E) A) For Ellipse E<1 B) For Parabola E=1 C) For Hyperbola E>1 Refer Problem nos. -
Brief Information on the Surfaces Not Included in the Basic Content of the Encyclopedia
Brief Information on the Surfaces Not Included in the Basic Content of the Encyclopedia Brief information on some classes of the surfaces which cylinders, cones and ortoid ruled surfaces with a constant were not picked out into the special section in the encyclo- distribution parameter possess this property. Other properties pedia is presented at the part “Surfaces”, where rather known of these surfaces are considered as well. groups of the surfaces are given. It is known, that the Plücker conoid carries two-para- At this section, the less known surfaces are noted. For metrical family of ellipses. The straight lines, perpendicular some reason or other, the authors could not look through to the planes of these ellipses and passing through their some primary sources and that is why these surfaces were centers, form the right congruence which is an algebraic not included in the basic contents of the encyclopedia. In the congruence of the4th order of the 2nd class. This congru- basis contents of the book, the authors did not include the ence attracted attention of D. Palman [8] who studied its surfaces that are very interesting with mathematical point of properties. Taking into account, that on the Plücker conoid, view but having pure cognitive interest and imagined with ∞2 of conic cross-sections are disposed, O. Bottema [9] difficultly in real engineering and architectural structures. examined the congruence of the normals to the planes of Non-orientable surfaces may be represented as kinematics these conic cross-sections passed through their centers and surfaces with ruled or curvilinear generatrixes and may be prescribed a number of the properties of a congruence of given on a picture. -
Parametric Surfaces and 16.6 Their Areas Parametric Surfaces
Parametric Surfaces and 16.6 Their Areas Parametric Surfaces 2 Parametric Surfaces Similarly to describing a space curve by a vector function r(t) of a single parameter t, a surface can be expressed by a vector function r(u, v) of two parameters u and v. Suppose r(u, v) = x(u, v)i + y(u, v)j + z(u, v)k is a vector-valued function defined on a region D in the uv-plane. So x, y, and, z, the component functions of r, are functions of the two variables u and v with domain D. The set of all points (x, y, z) in R3 s.t. x = x(u, v), y = y(u, v), z = z(u, v) and (u, v) varies throughout D, is called a parametric surface S. Typical surfaces: Cylinders, spheres, quadric surfaces, etc. 3 Example 3 – Important From Book The vector equation of a plane through (x0, y0, z0) and containing vectors is rather 4 Example – Point on Surface? Does the point (2, 3, 3) lie on the given surface? How about (1, 2, 1)? 5 Example – Identify the Surface Identify the surface with the given vector equation. 6 Example – Identify the Surface Identify the surface with the given vector equation. 7 Example – Find a Parametric Equation The part of the hyperboloid –x2 – y2 + z = 1 that lies below the rectangle [–1, 1] X [–3, 3]. 8 Example – Find a Parametric Equation The part of the cylinder x2 + z2 = 1 that lies between the planes y = 1 and y = 3. 9 Example – Find a Parametric Equation Part of the plane z = 5 that lies inside the cylinder x2 + y2 = 16. -
A Characterization of Helical Polynomial Curves of Any Degree
A CHARACTERIZATION OF HELICAL POLYNOMIAL CURVES OF ANY DEGREE J. MONTERDE Abstract. We give a full characterization of helical polynomial curves of any degree and a simple way to construct them. Existing results about Hermite interpolation are revisited. A simple method to select the best quintic interpolant among all possible solutions is suggested. 1. Introduction The notion of helical polynomial curves, i.e, polynomial curves which made a constant angle with a ¯xed line in space, have been studied by di®erent authors. Let us cite the papers [5, 6, 7] where the main results about the cubical and quintic cases are stablished. In [5] the authors gives a necessary condition a polynomial curve must satisfy in order to be a helix. The condition is expressed in terms of its hodograph, i.e., its derivative. If a polynomial curve, ®, is a helix then its hodograph, ®0, must be Pythagorean, i.e., jj®0jj2 is a perfect square of a polynomial. Moreover, this condition is su±cient in the cubical case: all PH cubical curves are helices. In the same paper it is also stated that not only ®0 must be Pythagorean, but also ®0^®00. Following the same ideas, in [1] it is proved that both conditions are su±cient in the quintic case. Unfortunately, this characterization is no longer true for higher degrees. It is possible to construct examples of polynomial curves of degree 7 verifying both conditions but being not a helix. The aim of this paper is just to show how a simple geometric trick can clarify the proofs of some previous results and to simplify the needed compu- tations to solve some related problems as for instance, the Hermite problem using helical polynomial curves. -
Linguistic Presentation of Objects
Zygmunt Ryznar dr emeritus Cracow Poland [email protected] Linguistic presentation of objects (types,structures,relations) Abstract Paper presents phrases for object specification in terms of structure, relations and dynamics. An applied notation provides a very concise (less words more contents) description of object. Keywords object relations, role, object type, object dynamics, geometric presentation Introduction This paper is based on OSL (Object Specification Language) [3] dedicated to present the various structures of objects, their relations and dynamics (events, actions and processes). Jay W.Forrester author of fundamental work "Industrial Dynamics”[4] considers the importance of relations: “the structure of interconnections and the interactions are often far more important than the parts of system”. Notation <!...> comment < > container of (phrase,name...) ≡> link to something external (outside of definition)) <def > </def> start-end of definition <spec> </spec> start-end of specification <beg> <end> start-end of section [..] or {..} 1 list of assigned keywords :[ or :{ structure ^<name> optional item (..) list of items xxxx(..) name of list = value assignment @ mark of special attribute,feature,property @dark unknown, to obtain, to discover :: belongs to : equivalent name (e.g.shortname) # number of |name| executive/operational object ppppXxxx name of item Xxxx with prefix ‘pppp ‘ XXXX basic object UUUU.xxxx xxxx object belonged to UUUU object class & / conjunctions ‘and’ ‘or’ 1 If using Latex editor we suggest [..] brackets -
Semiflexible Polymers
Semiflexible Polymers: Fundamental Theory and Applications in DNA Packaging Thesis by Andrew James Spakowitz In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy California Institute of Technology MC 210-41 Caltech Pasadena, California 91125 2004 (Defended September 28, 2004) ii c 2004 Andrew James Spakowitz All Rights Reserved iii Acknowledgements Over the last five years, I have benefitted greatly from my interactions with many people in the Caltech community. I am particularly grateful to the members of my thesis committee: John Brady, Rob Phillips, Niles Pierce, and David Tirrell. Their example has served as guidance in my scientific development, and their professional assistance and coaching have proven to be invaluable in my future career plans. Our collaboration has impacted my research in many ways and will continue to be fruitful for years to come. I am grateful to my research advisor, Zhen-Gang Wang. Throughout my scientific development, Zhen-Gang’s ongoing patience and honesty have been instrumental in my scientific growth. As a researcher, his curiosity and fearlessness have been inspirational in developing my approach and philosophy. As an advisor, he serves as a model that I will turn to throughout the rest of my career. Throughout my life, my family’s love, encouragement, and understanding have been of utmost importance in my development, and I thank them for their ongoing devotion. My friends have provided the support and, at times, distraction that are necessary in maintaining my sanity; for this, I am thankful. Finally, I am thankful to my fianc´ee, Sarah Heilshorn, for her love, support, encourage- ment, honesty, critique, devotion, and wisdom. -
Multivariable and Vector Calculus
Multivariable and Vector Calculus Lecture Notes for MATH 0200 (Spring 2015) Frederick Tsz-Ho Fong Department of Mathematics Brown University Contents 1 Three-Dimensional Space ....................................5 1.1 Rectangular Coordinates in R3 5 1.2 Dot Product7 1.3 Cross Product9 1.4 Lines and Planes 11 1.5 Parametric Curves 13 2 Partial Differentiations ....................................... 19 2.1 Functions of Several Variables 19 2.2 Partial Derivatives 22 2.3 Chain Rule 26 2.4 Directional Derivatives 30 2.5 Tangent Planes 34 2.6 Local Extrema 36 2.7 Lagrange’s Multiplier 41 2.8 Optimizations 46 3 Multiple Integrations ........................................ 49 3.1 Double Integrals in Rectangular Coordinates 49 3.2 Fubini’s Theorem for General Regions 53 3.3 Double Integrals in Polar Coordinates 57 3.4 Triple Integrals in Rectangular Coordinates 62 3.5 Triple Integrals in Cylindrical Coordinates 67 3.6 Triple Integrals in Spherical Coordinates 70 4 Vector Calculus ............................................ 75 4.1 Vector Fields on R2 and R3 75 4.2 Line Integrals of Vector Fields 83 4.3 Conservative Vector Fields 88 4.4 Green’s Theorem 98 4.5 Parametric Surfaces 105 4.6 Stokes’ Theorem 120 4.7 Divergence Theorem 127 5 Topics in Physics and Engineering .......................... 133 5.1 Coulomb’s Law 133 5.2 Introduction to Maxwell’s Equations 137 5.3 Heat Diffusion 141 5.4 Dirac Delta Functions 144 1 — Three-Dimensional Space 1.1 Rectangular Coordinates in R3 Throughout the course, we will use an ordered triple (x, y, z) to represent a point in the three dimensional space. -
Math 1300 Section 4.8: Parametric Equations A
MATH 1300 SECTION 4.8: PARAMETRIC EQUATIONS A parametric equation is a collection of equations x = x(t) y = y(t) that gives the variables x and y as functions of a parameter t. Any real number t then corresponds to a point in the xy-plane given by the coordi- nates (x(t); y(t)). If we think about the parameter t as time, then we can interpret t = 0 as the point where we start, and as t increases, the parametric equation traces out a curve in the plane, which we will call a parametric curve. (x(t); y(t)) • The result is that we can \draw" curves just like an Etch-a-sketch! animated parametric circle from wolfram Date: 11/06. 1 4.8 2 Let's consider an example. Suppose we have the following parametric equation: x = cos(t) y = sin(t) We know from the pythagorean theorem that this parametric equation satisfies the relation x2 + y2 = 1 , so we see that as t varies over the real numbers we will trace out the unit circle! Lets look at the curve that is drawn for 0 ≤ t ≤ π. Just picking a few values we can observe that this parametric equation parametrizes the upper semi-circle in a counter clockwise direction. (0; 1) • t x(t) y(t) 0 1 0 p p π 2 2 •(1; 0) 4 2 2 π 2 0 1 π -1 0 Looking at the curve traced out over any interval of time longer that 2π will indeed trace out the entire circle. -
Calculus Terminology
AP Calculus BC Calculus Terminology Absolute Convergence Asymptote Continued Sum Absolute Maximum Average Rate of Change Continuous Function Absolute Minimum Average Value of a Function Continuously Differentiable Function Absolutely Convergent Axis of Rotation Converge Acceleration Boundary Value Problem Converge Absolutely Alternating Series Bounded Function Converge Conditionally Alternating Series Remainder Bounded Sequence Convergence Tests Alternating Series Test Bounds of Integration Convergent Sequence Analytic Methods Calculus Convergent Series Annulus Cartesian Form Critical Number Antiderivative of a Function Cavalieri’s Principle Critical Point Approximation by Differentials Center of Mass Formula Critical Value Arc Length of a Curve Centroid Curly d Area below a Curve Chain Rule Curve Area between Curves Comparison Test Curve Sketching Area of an Ellipse Concave Cusp Area of a Parabolic Segment Concave Down Cylindrical Shell Method Area under a Curve Concave Up Decreasing Function Area Using Parametric Equations Conditional Convergence Definite Integral Area Using Polar Coordinates Constant Term Definite Integral Rules Degenerate Divergent Series Function Operations Del Operator e Fundamental Theorem of Calculus Deleted Neighborhood Ellipsoid GLB Derivative End Behavior Global Maximum Derivative of a Power Series Essential Discontinuity Global Minimum Derivative Rules Explicit Differentiation Golden Spiral Difference Quotient Explicit Function Graphic Methods Differentiable Exponential Decay Greatest Lower Bound Differential -
Eukaryotic Genome Annotation
Comparative Features of Multicellular Eukaryotic Genomes (2017) (First three statistics from www.ensembl.org; other from original papers) C. elegans A. thaliana D. melanogaster M. musculus H. sapiens Species name Nematode Thale Cress Fruit Fly Mouse Human Size (Mb) 103 136 143 3,482 3,555 # Protein-coding genes 20,362 27,655 13,918 22,598 20,338 (25,498 (13,601 original (30,000 (30,000 original est.) original est.) original est.) est.) Transcripts 58,941 55,157 34,749 131,195 200,310 Gene density (#/kb) 1/5 1/4.5 1/8.8 1/83 1/97 LINE/SINE (%) 0.4 0.5 0.7 27.4 33.6 LTR (%) 0.0 4.8 1.5 9.9 8.6 DNA Elements 5.3 5.1 0.7 0.9 3.1 Total repeats 6.5 10.5 3.1 38.6 46.4 Exons % genome size 27 28.8 24.0 per gene 4.0 5.4 4.1 8.4 8.7 average size (bp) 250 506 Introns % genome size 15.6 average size (bp) 168 Arabidopsis Chromosome Structures Sorghum Whole Genome Details Characterizing the Proteome The Protein World • Sequencing has defined o Many, many proteins • How can we use this data to: o Define genes in new genomes o Look for evolutionarily related genes o Follow evolution of genes ▪ Mixing of domains to create new proteins o Uncover important subsets of genes that ▪ That deep phylogenies • Plants vs. animals • Placental vs. non-placental animals • Monocots vs. dicots plants • Common nomenclature needed o Ensure consistency of interpretations InterPro (http://www.ebi.ac.uk/interpro/) Classification of Protein Families • Intergrated documentation resource for protein super families, families, domains and functional sites o Mitchell AL, Attwood TK, Babbitt PC, et al. -
STACK: a Toolkit for Analysing Β-Helix Proteins
STACK: a toolkit for analysing ¯-helix proteins Master of Science Thesis (20 points) Salvatore Cappadona, Lars Diestelhorst Abstract ¯-helix proteins contain a solenoid fold consisting of repeated coils forming parallel ¯-sheets. Our goal is to formalise the intuitive notion of a ¯-helix in an objective algorithm. Our approach is based on first identifying residues stacks — linear spatial arrangements of residues with similar conformations — and then combining these elementary patterns to form ¯-coils and ¯-helices. Our algorithm has been implemented within STACK, a toolkit for analyzing ¯-helix proteins. STACK distinguishes aromatic, aliphatic and amidic stacks such as the asparagine ladder. Geometrical features are computed and stored in a relational database. These features include the axis of the ¯-helix, the stacks, the cross-sectional shape, the area of the coils and related packing information. An interface between STACK and a molecular visualisation program enables structural features to be highlighted automatically. i Contents 1 Introduction 1 2 Biological Background 2 2.1 Basic Concepts of Protein Structure ....................... 2 2.2 Secondary Structure ................................ 2 2.3 The ¯-Helix Fold .................................. 3 3 Parallel ¯-Helices 6 3.1 Introduction ..................................... 6 3.2 Nomenclature .................................... 6 3.2.1 Parallel ¯-Helix and its ¯-Sheets ..................... 6 3.2.2 Stacks ................................... 8 3.2.3 Coils ..................................... 8 3.2.4 The Core Region .............................. 8 3.3 Description of Known Structures ......................... 8 3.3.1 Helix Handedness .............................. 8 3.3.2 Right-Handed Parallel ¯-Helices ..................... 13 3.3.3 Left-Handed Parallel ¯-Helices ...................... 19 3.4 Amyloidosis .................................... 20 4 The STACK Toolkit 24 4.1 Identification of Structural Elements ....................... 24 4.1.1 Stacks ................................... -
Calculating the Structure-Based Phylogenetic Relationship
CALCULATING THE STRUCTURE-BASED PHYLOGENETIC RELATIONSHIP OF DISTANTLY RELATED HOMOLOGOUS PROTEINS UTILIZING MAXIMUM LIKELIHOOD STRUCTURAL ALIGNMENT COMBINATORICS AND A NOVEL STRUCTURAL MOLECULAR CLOCK HYPOTHESIS A DISSERTATION IN Molecular Biology and Biochemistry and Cell Biology and Biophysics Presented to the Faculty of the University of Missouri-Kansas City in partial fulfillment of the requirements for the degree Doctor of Philosophy by SCOTT GARRETT FOY B.S., Southwest Baptist University, 2005 B.A., Truman State University, 2007 M.S., University of Missouri-Kansas City, 2009 Kansas City, Missouri 2013 © 2013 SCOTT GARRETT FOY ALL RIGHTS RESERVED CALCULATING THE STRUCTURE-BASED PHYLOGENETIC RELATIONSHIP OF DISTANTLY RELATED HOMOLOGOUS PROTEINS UTILIZING MAXIMUM LIKELIHOOD STRUCTURAL ALIGNMENT COMBINATORICS AND A NOVEL STRUCTURAL MOLECULAR CLOCK HYPOTHESIS Scott Garrett Foy, Candidate for the Doctor of Philosophy Degree University of Missouri-Kansas City, 2013 ABSTRACT Dendrograms establish the evolutionary relationships and homology of species, proteins, or genes. Homology modeling, ligand binding, and pharmaceutical testing all depend upon the homology ascertained by dendrograms. Regardless of the specific algorithm, all dendrograms that ascertain protein evolutionary homology are generated utilizing polypeptide sequences. However, because protein structures superiorly conserve homology and contain more biochemical information than their associated protein sequences, I hypothesize that utilizing the structure of a protein instead