Taxonomy: an Introduction to Classification
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Quantum in the Cloud: Application Potentials and Research Opportunities
Quantum in the Cloud: Application Potentials and Research Opportunities Frank Leymann a, Johanna Barzen b, Michael Falkenthal c, Daniel Vietz d, Benjamin Weder e and Karoline Wild f Institute of Architecture of Application Systems, University of Stuttgart, Universitätsstr. 38, Stuttgart, Germany Keywords: Cloud Computing, Quantum Computing, Hybrid Applications. Abstract: Quantum computers are becoming real, and they have the inherent potential to significantly impact many application domains. We sketch the basics about programming quantum computers, showing that quantum programs are typically hybrid consisting of a mixture of classical parts and quantum parts. With the advent of quantum computers in the cloud, the cloud is a fine environment for performing quantum programs. The tool chain available for creating and running such programs is sketched. As an exemplary problem we discuss efforts to implement quantum programs that are hardware independent. A use case from machine learning is outlined. Finally, a collaborative platform for solving problems with quantum computers that is currently under construction is presented. 1 INTRODUCTION Because of this, the overall algorithms are often hybrid. They perform parts on a quantum computer, Quantum computing advanced up to a state that urges other parts on a classical computer. Each part attention to the software community: problems that performed on a quantum computer is fast enough to are hard to solve based on classical (hardware and produce reliable results. The parts executed on a software) technology become tractable in the next classical computer analyze the results, compute new couple of years (National Academies, 2019). parameters for the quantum parts, and pass them on Quantum computers are offered for commercial use to a quantum part. -
Synthesis of Phylogeny and Taxonomy Into a Comprehensive Tree of Life
Synthesis of phylogeny and taxonomy into a comprehensive tree of life Cody E. Hinchliffa,1, Stephen A. Smitha,1,2, James F. Allmanb, J. Gordon Burleighc, Ruchi Chaudharyc, Lyndon M. Coghilld, Keith A. Crandalle, Jiabin Dengc, Bryan T. Drewf, Romina Gazisg, Karl Gudeh, David S. Hibbettg, Laura A. Katzi, H. Dail Laughinghouse IVi, Emily Jane McTavishj, Peter E. Midfordd, Christopher L. Owenc, Richard H. Reed, Jonathan A. Reesk, Douglas E. Soltisc,l, Tiffani Williamsm, and Karen A. Cranstonk,2 aEcology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109; bInterrobang Corporation, Wake Forest, NC 27587; cDepartment of Biology, University of Florida, Gainesville, FL 32611; dField Museum of Natural History, Chicago, IL 60605; eComputational Biology Institute, George Washington University, Ashburn, VA 20147; fDepartment of Biology, University of Nebraska-Kearney, Kearney, NE 68849; gDepartment of Biology, Clark University, Worcester, MA 01610; hSchool of Journalism, Michigan State University, East Lansing, MI 48824; iBiological Science, Clark Science Center, Smith College, Northampton, MA 01063; jDepartment of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045; kNational Evolutionary Synthesis Center, Duke University, Durham, NC 27705; lFlorida Museum of Natural History, University of Florida, Gainesville, FL 32611; and mComputer Science and Engineering, Texas A&M University, College Station, TX 77843 Edited by David M. Hillis, The University of Texas at Austin, Austin, TX, and approved July 28, 2015 (received for review December 3, 2014) Reconstructing the phylogenetic relationships that unite all line- published phylogenies are available only as journal figures, rather ages (the tree of life) is a grand challenge. The paucity of homologous than in electronic formats that can be integrated into databases and character data across disparately related lineages currently renders synthesis methods (7–9). -
Biology Assessment Plan Spring 2019
Biological Sciences Department 1 Biology Assessment Plan Spring 2019 Task: Revise the Biology Program Assessment plans with the goal of developing a sustainable continuous improvement plan. In order to revise the program assessment plan, we have been asked by the university assessment committee to revise our Students Learning Outcomes (SLOs) and Program Learning Outcomes (PLOs). Proposed revisions Approach: A large community of biology educators have converged on a set of core biological concepts with five core concepts that all biology majors should master by graduation, namely 1) evolution; 2) structure and function; 3) information flow, exchange, and storage; 4) pathways and transformations of energy and matter; and (5) systems (Vision and Change, AAAS, 2011). Aligning our student learning and program goals with Vision and Change (V&C) provides many advantages. For example, the V&C community has recently published a programmatic assessment to measure student understanding of vision and change core concepts across general biology programs (Couch et al. 2019). They have also carefully outlined student learning conceptual elements (see Appendix A). Using the proposed assessment will allow us to compare our student learning profiles to those of similar institutions across the country. Revised Student Learning Objectives SLO 1. Students will demonstrate an understanding of core concepts spanning scales from molecules to ecosystems, by analyzing biological scenarios and data from scientific studies. Students will correctly identify and explain the core biological concepts involved relative to: biological evolution, structure and function, information flow, exchange, and storage, the pathways and transformations of energy and matter, and biological systems. More detailed statements of the conceptual elements students need to master are presented in appendix A. -
Principles of Plant Taxonomy Bot
PRINCIPLES OF PLANT TAXONOMY BOT 222 Dr. M. Ajmal Ali, PhD 1 What is Taxonomy / Systematics ? Animal group No. of species Amphibians 6,199 Birds 9,956 Fish 30,000 Mammals 5,416 Tundra Reptiles 8,240 Subtotal 59,811 Grassland Forest Insects 950,000 Molluscs 81,000 Q: Why we keep the stuffs of our home Crustaceans 40,000 at the fixed place or arrange into some Corals 2,175 kinds of system? Desert Others 130,200 Rain forest Total 1,203,375 • Every Human being is a Taxonomist Plants No. of species Mosses 15,000 Ferns and allies 13,025 Gymnosperms 980 Dicotyledons 199,350 Monocotyledons 59,300 Green Algae 3,715 Red Algae 5,956 Lichens 10,000 Mushrooms 16,000 Brown Algae 2,849 Subtotal 28,849 Total 1,589,361 • We have millions of different kind of plants, animals and microorganism. We need to scientifically identify, name and classify all the living organism. • Taxonomy / Systematics is the branch of science deals with classification of organism. 2 • Q. What is Plant Taxonomy / Plant systematics We study plants because: Plants convert Carbon dioxide gas into Every things we eat comes Plants produce oxygen. We breathe sugars through the process of directly or indirectly from oxygen. We cannot live without photosynthesis. plants. oxygen. Many chemicals produced by the Study of plants science helps to Study of plants science helps plants used as learn more about the natural Plants provide fibres for paper or fabric. to conserve endangered medicine. world plants. We have millions of different kind of plants, animals and microorganism. -
The Taxonomy of Human Evolved Psychological Adaptations
Evo Edu Outreach (2012) 5:312–320 DOI 10.1007/s12052-012-0428-8 EVOLUTION AND EDUCATION RESOURCES PsychTable.org: The Taxonomy of Human Evolved Psychological Adaptations Niruban Balachandran & Daniel J. Glass Published online: 8 July 2012 # Springer Science+Business Media, LLC 2012 Abstract We announce the launch of PsychTable.org,a Introduction collaborative web-based project devoted to classifying and evaluating evolved psychological adaptations The timing is right to establish a classification system for (EPAs), geared toward researchers, educators, students, human evolved psychological adaptations (EPAs). Several and the general public. The website works by aggregat- factors have coalesced to create a unique opportunity to de- ing citations which support or challenge the existence of velop a taxonomy that will facilitate the expansion of a culture each purported EPA, using a mathematical algorithm to of both synthesis and empirical rigor in the evolutionary assign an evidentiary strength score to each, and gener- behavioral sciences, including disciplines such as evolution- ating a table which represents the current but ever- ary cognitive neuroscience, behavioral ecology, “evo-devo,” changing state of the empirical evidence. Citations are primatology, evolutionary anthropology, human ethology, ge- added and assigned evaluative ratings by both general netics, and others. users and an international community of expert contrib- These aforementioned factors include: a large international utors; as such, the content of the site will represent the body of research describing hundreds of amassed EPAs; a consensus of the scientific community and new research global research community of evolutionary behavioral scien- opportunities. PsychTable has features for achieving empir- tists that recognizes the importance of both synthesis and ical meta-goals such as quality control, hypothesis testing, classification; the ascent of evolutionary psychology as a cross-disciplinary collaboration, and didactic utility. -
Transfer of the Type Species of the Genus Themobacteroides to the Genus Themoanaerobacter As Themoanaerobacter Acetoethylicus (Ben-Bassat and Zeikus 1981) Comb
INTERNATIONAL JOURNAL OF SYSTEMATICBACTERIOLOGY, Oct. 1993, p. 857-859 Vol. 43, No. 4 0020-7713/93/040857-03$02.00/0 Copyright 0 1993, International Union of Microbiological Societies Transfer of the Type Species of the Genus Themobacteroides to the Genus Themoanaerobacter as Themoanaerobacter acetoethylicus (Ben-Bassat and Zeikus 1981) comb. nov., Description of Coprothemobacter gen. nov., and Reclassification of Themobacteroides proteolyticus as Coprothennobacter proteolyticus (Ollivier et al. 1985) comb. nov. FRED A. RAINEY AND ERKO STACKEBRANDT* DSM-Deutsche Sammlung von Mikroolganisrnen und Zellkulturen, Mascheroder Weg lb, 38124 Braunschweig, Germany Phylogenetic and phenotypic evidence demonstrates the taxonomic heterogeneity of the genus Thennobac- teroides and indicates a close relationship between Thennobacteroides acetoethylicus and members of the genus Thennoanaerobacter. Since T. acetoethylicus is the type species of Thennobacteroides, its removal invalidates the genus. As a consequence, the remaining species Thennobacteroides proteolyticus is proposed as the type species of the new genus Coprothennobacter gen. nov., as Coprothennobacter proteolyticus comb. nov. Recent phylogenetic studies (8, 9) of anaerobic thermo- hybridization studies with all members of Thermoanaero- philic species demonstrated that the majority of strains fall bacter (6, 10) despite the fact that, like Thermoanaerobacter within the phylogenetic confines of the Clostridium-Bacillus species, Thermobacteroides acetoethylicus is an anaerobic, subphylum of gram-positive bacteria. In contrast to the thermophilic, glycolytic bacterium capable of growth above phylog enet ically coherent genera Thermoana erobac ter (6) 70°C that has been isolated from geothermal environments. and Thermoanaerobacterium (6), members of Thermobac- The reclassifications of the recent study of Lee et al. (6) teroides (1,7) belonged to phylogenetically very diverse taxa increased the numbers of species of Thermoanaerobacter to (8). -
Introduction to Botany
Introduction to Botany Jan Zientek Senior Program Coordinator Cooperative Extension of Essex County [email protected] Basic Botany • The study of the growth, structure and function of plants Plant Functions BOTANY • Evolution • Taxonomy • Plant morphology • Plant physiology and cell biology • Plant reproduction • Plant hormones and growth regulators PLANTAE • Eukaryotic (with a • Chloroplasts nucleus) (green) • Cell walls with • Non-motile cellulose • Several phlyum • Food stored as • Development of carbohydrate pollen • Multi-cellular autotrophs DOMAIN KINGDOM PHYLUM CLASS ORDER FAMILY Genus species Plant phylums Mosses Cycads Liverworts Ginkgoes Hornworts Gnetophytes Club mosses Conifers Horsetails Ferns Common Name vs Scientific Name Foxglove Digitalis purpurea • Maybe local name • Universally recognized • General • Specific Common Name vs Scientific Name Fire bush Scarlet bush Texas firecracker Corail (or is it Koray?) Hamelia patens Polly red head Hummingbird bush Ix-canan Plant Types • Monocots: have a single cotyledon, flower parts in multiples of three, parallel venation of leaves, scattered vascular bundles in stems. Dicots: have two cotyledons, flower parts in multiples of 4 or 5, netted veins, and stems which are organized in a ring pattern. Humans sort things many different ways • Plants can be classified by the type of their seed structure – Gymnosperm: “naked seed” – Angiosperm: seed within a fruiting body • Lifecycles help gardeners distinguish between plants: • Annuals • Biennials • Perennials Annuals complete life cycles in one season Biennials live for 2 years, flower, then die Perennials live for 3 or more years, flower each year and usually do not die after flowering. Structures of Plants Roots Stems Leaves Flowers Seeds Examples of Stem Structure Herbaceous monocot and dicot stem Root cross-section • Apical meristem: point of vigorous cell division and growth. -
Re-Description of the Sauropod Dinosaur Amanzia (“Ornithopsis
Schwarz et al. Swiss J Geosci (2020) 113:2 https://doi.org/10.1186/s00015-020-00355-5 Swiss Journal of Geosciences ORIGINAL PAPER Open Access Re-description of the sauropod dinosaur Amanzia (“Ornithopsis/Cetiosauriscus”) greppini n. gen. and other vertebrate remains from the Kimmeridgian (Late Jurassic) Reuchenette Formation of Moutier, Switzerland Daniela Schwarz1* , Philip D. Mannion2 , Oliver Wings3 and Christian A. Meyer4 Abstract Dinosaur remains were discovered in the 1860’s in the Kimmeridgian (Late Jurassic) Reuchenette Formation of Moutier, northwestern Switzerland. In the 1920’s, these were identifed as a new species of sauropod, Ornithopsis greppini, before being reclassifed as a species of Cetiosauriscus (C. greppini), otherwise known from the type species (C. stewarti) from the late Middle Jurassic (Callovian) of the UK. The syntype of “C. greppini” consists of skeletal elements from all body regions, and at least four individuals of diferent sizes can be distinguished. Here we fully re-describe this material, and re-evaluate its taxonomy and systematic placement. The Moutier locality also yielded a theropod tooth, and fragmen- tary cranial and vertebral remains of a crocodylomorph, also re-described here. “C.” greppini is a small-sized (not more than 10 m long) non-neosauropod eusauropod. Cetiosauriscus stewarti and “C.” greppini difer from each other in: (1) size; (2) the neural spine morphology and diapophyseal laminae of the anterior caudal vertebrae; (3) the length-to-height proportion in the middle caudal vertebrae; (4) the presence or absence of ridges and crests on the middle caudal cen- tra; and (5) the shape and proportions of the coracoid, humerus, and femur. -
Anatomy and Go Fish! Background
Anatomy and Go Fish! Background Introduction It is important to properly identify fi sh for many reasons: to follow the rules and regulations, for protection against sharp teeth or protruding spines, for the safety of the fi sh, and for consumption or eating purposes. When identifying fi sh, scientists and anglers use specifi c vocabulary to describe external or outside body parts. These body parts are common to most fi sh. The difference in the body parts is what helps distinguish one fi sh from another, while their similarities are used to classify them into groups. There are approximately 29,000 fi sh species in the world. In order to identify each type of fi sh, scientists have grouped them according to their outside body parts, specifi cally the number and location of fi ns, and body shape. Classifi cation Using a system of classifi cation, scientists arrange all organisms into groups based on their similarities. The fi rst system of classifi cation was proposed in 1753 by Carolus Linnaeus. Linnaeus believed that each organism should have a binomial name, genus and species, with species being the smallest organization unit of life. Using Linnaeus’ system as a guide, scientists created a hierarchical system known as taxonomic classifi cation, in which organisms are classifi ed into groups based on their similarities. This hierarchical system moves from largest and most general to smallest and most specifi c: kingdom, phylum, class, order, family, genus, and species. {See Figure 1. Taxonomic Classifi cation Pyramid}. For example, fi sh belong to the kingdom Animalia, the phylum Chordata, and from there are grouped more specifi cally into several classes, orders, families, and thousands of genus and species. -
An Application to Biology
Physical Science & Biophysics Journal ISSN: 2641-9165 Information as Order Hidden within Chance: An Application to Biology Strumia A* Review Article Istituto Nazionale di Alta Matematica "Francesco Severi", Italy Volume 3 Issue 3 *Corresponding author: Alberto Strumia, Istituto Nazionale di Alta Matematica Received Date: August 12, 2019 Published Date: August 27, 2019 "Francesco Severi", Italy, Email: [email protected] Abstract We show, by didactical examples, how algorithmic information (coded e.g., into a computer program) is required to build the structure of an organized system (either simple or complex). Ordered structures can be obtained as attractors both by some dynamics starting from sequential initial conditions (order from order) and by some dynamics starting from random initial conditions (order from chance) provided that a leading algorithmic information is assigned to govern the evolution of the generating process. In absence of information emergence of some ordered structure, like e.g., an organ of a living system is so highly improbable to be impossible in practice. We provide didactical examples of static models of a human heart, each generated starting either from ordered initial conditions, or from random sparse initial conditions, or more realistically by random cellular automata (so that any mother cell is allowed to generate a daughter cell only in a random contiguous location). Significantly, as it was pointed out by Gregory Chaitin, not all algorithmic information can be compressed into a string shorter than the sequence of its original individual code digits (incompressible information string). A question is still open about the DNA and, more generally, any biological information: is it to be considered as a compressible or an incompressible code string? In our example of anatomic human heart model we have treated the sequence of the co-ordinates of each sphere (roughly modeling a cell) as an uncompressed string, while a compressed program string seems to be able to provide only less realistic models. -
The Hessian Fly in California
". ~. .: "" ~ .- - - " .... ,' ~ .-,. '-' .. :'.~'~' ;::-" - ~ '"' - "'= -, ..... ~~~ ~-~ ',' I~ 111112.~ 2 5 I~ 2 5 W 1= 11111 . 1I11~ 11111 . 1.0 3 2 w W 1 . W ~3.2 .2 II ~ ~ t.:.: Ii.£ t.:.: w w I~ I:: I:: '" ~ ... I~ 1.1 '"..;a~~ " 1.1 I..a.:.""0.::. " - 111111.25 111111.4 111111.6 111111.25 111111.4 111111.6 MICROCOPY RESOLUTION TEST CHART MICROCOPY RESOLUTION TEST \Alh~T NATIONAL BUREAU Of STANOARDS-1963-A NATIONAL BUREAU Of STANDARDS-1963-A . )"' :~);. UNiTED'ST{1TESi)E~~~~ 9F;AG~CUL~' . WASHINGTON, D. C. ' .... ~THE HESsiAN FLY I~ ·CALIFQR.NIA!), .;~4 ,." e ~ ~ 7~,' ; ~ " } uy C. M. PACJtAJili; 'Seni6r'iiintomQlogist, D£",iiWn of Om-eta and-Forage 1ft86'*s,. 1 <.;:t"" ' ,Bureau of EntOfniJpJw " ; ." . coNTENTs ' Page' PIige Ee6nomfe fmportSnce..,.. .._,..,._.; _____ '-, t Met~~!oglcal"Summer mortalitY' control~Contbiued. __________ _ History________---"-"-..:-------..:..--- 3 Artificial 16 Seasonal lilstory________________.. 4 controL____ .:_.;·________ _ -l7 Character of Injury______________ 7 Burning. stubble _______-' ____ _ 17 Development _____________________ 10 Burying stubble by plowlug ___ _ 17 Summer' cultivation 'of stubble":_ 18 " ~~: l:~k:::::=::=:::::::::::::::::::::::: J~ Spraying stubble to.kill pUI!tlrlll- 19 Early plantlng_______________ _ 20 . ~~: f~::::::::::::::::::::::::::::::::=:::: ' . ~ Rotation of crops ____________ _ 20 SummaryPlanting._____________________ resistant. varletles_____ . 20 ~~~sft~~n~~_~_~'_~:r..<>~~~::::::::::=:::::: U Literature cited _____.. _____ .:.____ _ 24 Meteorological controL____________ 15 2:; . Early spring mortality_______ 15 c ':J .' ECONOl\IIC IMPORTANCE In Californin, the H~~ian fly (PhytopMga' dest'MtCtor Say) is of economic' importance O)~Y in wheat.,growing regions near ti,.e coast, where the influence oi' :the ocean is .sufficient to prevent eXtremely high" summer temperatu~es. -
Taxonomy Development for Knowledge Management
Date : 24/07/2008 Taxonomy Development for Knowledge Management Mary Whittaker Librarian Boeing Library Services The Boeing Company PO Box 3707 M/C 62-LC Seattle WA 98124 +1-425-306-2086 +1-425-965-0119 [email protected] Kathryn Breininger Manager Boeing Reports Management Services The Boeing Company PO Box 3707 M/C 62-LC Seattle WA 98124 +1-425-965-0242 +1-425-512-4281 [email protected] Meeting: 138 Knowledge Management Simultaneous Interpretation: English, Arabic, Chinese, French, German, Russian and Spanish WORLD LIBRARY AND INFORMATION CONGRESS: 74TH IFLA GENERAL CONFERENCE AND COUNCIL 10-14 August 2008, Québec, Canada http://www.ifla.org/IV/ifla74/index.htm Abstract As librarians and information professionals, we are faced with solving a growing information overload problem. We strive to connect end users with the information they need. How can we better connect searchers to the vast amount of information to be found on the web? Information management principles and practices, taxonomies, and other controlled vocabularies serve as knowledge management tools that we can use to help organize content and make connections between people and the information they need. This paper focuses on the processes associated with taxonomy development, including how to determine the requirements, how to identify concepts, and how to develop a draft taxonomy. It also covers techniques for validating a taxonomy, processes for incorporating changes within a taxonomy, applying a taxonomy to content, and methods for maintaining a taxonomy over time. Throughout the paper, best practices associated with these process steps are highlighted. Page 1 Introduction Information overload continues to be a challenge for our end users.