Courbet 1..10
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Synthetic Biology Background: Systems Architecture and Biology Memory: DNA Storage Building a Biological CPU Conclusions
Overview of Synthetic Biology Background: Systems Architecture and Biology Memory: DNA Storage Building a Biological CPU Conclusions Synthetic Biology: DNA Digital Storage, Computation and the Organic Computer Alex Widdel University of Minnesota, Morris 1 / 27 Overview of Synthetic Biology Background: Systems Architecture and Biology Memory: DNA Storage Building a Biological CPU Conclusions Outline 1 Overview of Synthetic Biology 2 Background: Systems Architecture and Biology 3 Memory: DNA Storage 4 Building a Biological CPU 5 Conclusions 2 / 27 Overview of Synthetic Biology Background: Systems Architecture and Biology Memory: DNA Storage Building a Biological CPU Conclusions What is Synthetic Biology? Biology is viewed as technology. One central goal: construction of a universal bio-computer. A union of biology, computer science, and engineering. The interdisciplinary nature and youth of synthetic biology has led to debate over the term. 3 / 27 Overview of Synthetic Biology Background: Systems Architecture and Biology Memory: DNA Storage Building a Biological CPU Conclusions Background: Systems Architecture 4 / 27 Overview of Synthetic Biology Background: Systems Architecture and Biology Memory: DNA Storage Building a Biological CPU Conclusions Systems: Von Neumann Architecture Four parts: Memory Input/output device (IO) Control Unit Arithmetic Logic Unit (ALU) I Arithmetic I/O Logic O Memory Control 5 / 27 Overview of Synthetic Biology Background: Systems Architecture and Biology Memory: DNA Storage Building a Biological CPU Conclusions Background: Biology 6 / 27 Overview of Synthetic Biology Background: Systems Architecture and Biology Memory: DNA Storage Building a Biological CPU Conclusions Biology: DNA and Protein Synthesis Structure of DNA: DNA can encode bits in a way that is compatible with the way computers store information. -
The Emergency Severity Index
The Emergency Severity Index Jassin M. Jouria, MD Dr. Jassin M. Jouria is a medical doctor, professor of academic medicine, and medical author. He graduated from Ross University School of Medicine and has completed his clinical clerkship training in various teaching hospitals throughout New York, including King’s County Hospital Center and Brookdale Medical Center, among others. Dr. Jouria has passed all USMLE medical board exams, and has served as a test prep tutor and instructor for Kaplan. He has developed several medical courses and curricula for a variety of educational institutions. Dr. Jouria has also served on multiple levels in the academic field including faculty member and Department Chair. Dr. Jouria continues to serve as a Subject Matter Expert for several continuing education organizations covering multiple basic medical sciences. He has also developed several continuing medical education courses covering various topics in clinical medicine. Recently, Dr. Jouria has been contracted by the University of Miami/Jackson Memorial Hospital’s Department of Surgery to develop an e- module training series for trauma patient management. Dr. Jouria is currently authoring an academic textbook on Human Anatomy & Physiology. Abstract One of the main challenges encountered by emergency departments is determining how to appropriately triage patients. Although some systems only take into account a single determining factor, the Agency for Healthcare Research and Quality promotes a system that considers both the acuity of patients’ health care problems as well as the number of resources needed to treat them. This system provides emergency departments with a unique tool to ensure that the most at-risk patients are being seen and treated in the most efficient manner. -
TRANSCRIPT Applications
Presidential Commission for the Study of Bioethical Issues TRANSCRIPT Applications J. Craig Venter, Ph.D. Founder and President, J. Craig Venter Institute George Church, Ph.D. Professor of Genetics, Harvard Medical School Kristala L. J. Prather, Ph.D. Assistant Professor, Dept. of Chemical Engineering, Massachu- setts Institute of Technology Meeting 1, Session 2 July 8, 2010 Washington, D.C. Jim Wagner: Could we have our speakers come to the table. And if others could take their chairs, we’ll get under way. Thank you. Commission members, we need you as well, actually. I see them filter- ing up. I saw Nita out there. And there’s Bonnie in the back of the room. So that there is ample time for our speakers to present and for us to ask questions, let’s do get under way. Really, again, appreciate this morning’s conversation and the presenta- tions, helping us to — wow. Helping us to define what is and is not synthetic biology and to understand a little bit more about some of the science involved. This particular session, we are going to focus and we have asked our experts to focus more on applications. We’ll try to use a similar format. Have our speakers present for a brief period. You have the timer in front of you. Make sure after all of you have pre- sented the commission has time to ask questions. And then we’ll try to throw it open — not try to – we will, certainly, throw it open to the public for other questions they may have. -
Driving Diffusion of Scientific Innovation
Driving Diffusion of Scientific Innovation - The Role of Institutional Entrepreneurship and Open Science in Synthetic Biology Vom Promotionsausschuss der Technischen Universit¨at Hamburg-Harburg zur Erlangung des akademischen Grades Doktor der Wirtschafts- und Sozialwissenschaften (Dr. rer. pol.) genehmigte Dissertation von Giulio Barth aus M¨unster 2018 Advisors: Prof. Dr. C. Ihl, Prof. Dr. M. G. M¨ohrle Institute of Entrepreneurship, TUHH i Gutachter: Prof. Dr. C. Ihl Prof. Dr. M. G. Mohrle¨ Vorsitz: Prof. Dr. C. Luthje¨ Tag der mundlichen¨ Prufung:¨ 14. September 2018 ”Our victory: inevitable; our timing: uncertain.” (Drew Endy, Assistant Professor Stanford University) i Abstract Scientific innovations need to widely diffuse to fully exploit their potential. Prior research investigated levers on the diffusion of scientific innovation with particular interest on institutions, e.g., settings of property rights. As institutional theory lacks in explaining emergence and shaping of institu- tions, the institutional entrepreneur approach faces these limitations. Key actors combine logics from multiple fields and convince their social context of their ideas to legitimate the creation of new institutions and shape an emerging field. This thesis validates theories on institutional entrepreneurs and investigates the end-to process from diffusing a logic to the impact of an established insti- tution on scientific innovations in context of the emerging synthetic biology. The field is expected to introduce the 5th revolution and characterized by the central logic of making biology an engineering discipline. In chapter 4 theories on institutional entrepreneurs driving diffusion of in- stitutional logics to shape an emerging field are validated. To measure the social influence mechanisms, the heterogeneous diffusion model is adapted to the institutional logic. -
Protomag.Com // Summer 10
26 protomag.com // SUMMER 10 HOW TO DECIDE: A physician’s roundabout, intuitive way // determining diagnosis, dosage, prognosis through experience, trial and error // or a fleet of formulas // applying rules to data, expediting answers // and streamlining care? Logical 27 Medicine BY MEERA LEE SETHI // PHOTOGRAPHS BY MAURICIO ALEJO o nonmathematicians, the word algorithm (from a latinized version of the name of T the ninth-century Persian astronomer who wrote a treatise on calculation) may seem arcane and off-putting, its defini- tion difficult to pin down. Yet the thing itself, if not the term, pops up everywhere. Across the spec- trum of human activity, algorithms run vital decision-making processes behind the scenes. If you’ve taken out a home mort- gage, an algorithm was applied to your financial records to determine how to price your loan. If you were stranded after the eruption of Iceland’s Eyjafjallajökull volcano, algorithms were responsible for the rerouting of thousands of planes and crews to get you home. If you own a Volvo S60 sedan, algorithms are used to scan for pedestrians in your path and hit the brakes even if you don’t. In every modern industry, including medicine, algorithms rule. An algorithm is any step-by-step procedure that applies rules to data, producing an unambiguous solution to a prob- lem, and there is now a vast universe of clinical examples. The Medical Algorithm Project (MedAL), which stores peer- reviewed algorithms in an online database, contains more than 14,400. These tools can help physicians make diagnoses, choose treatments, calculate dosages, predict outcomes and monitor side effects. -
CBD/DSI/AHTEG/2018/1/3 12 January 2018
CBD Distr. GENERAL CBD/SBSTTA/22/INF/3 CBD/DSI/AHTEG/2018/1/3 12 January 2018 ENGLISH ONLY AD HOC TECHNICAL EXPERT GROUP ON SUBSIDIARY BODY ON SCIENTIFIC, DIGITAL SEQUENCE INFORMATION ON TECHNICAL AND TECHNOLOGICAL GENETIC RESOURCES ADVICE Montreal, Canada, 13-16 February 2018 Twenty-second meeting Item 3 of the provisional agenda** Montreal, Canada, 2-7 July 2018 Item 3 of the provisional agenda*** FACT-FINDING AND SCOPING STUDY ON DIGITAL SEQUENCE INFORMATION ON GENETIC RESOURCES IN THE CONTEXT OF THE CONVENTION ON BIOLOGICAL DIVERSITY AND THE NAGOYA PROTOCOL Note by the Executive Secretary 1. In decision XIII/16, paragraph 3(b), the Executive Secretary was requested to commission a fact-finding and scoping study, subject to the availability of funds, to clarify terminology and concepts and to assess the extent and the terms and conditions of the use of digital sequence information on genetic resources in the context of the Convention and the Nagoya Protocol. 2. Accordingly, the Executive Secretary commissioned a research team led by Ms. Sarah Laird of People and Plants International and Ms. Rachel Wynberg of the University of Cape Town, to carry out this study. The study was undertaken with the generous financial support of Canada, the European Union and Switzerland. 3. A draft of the study was made available online for peer review from 8 November to 1 December 2017. 1 The comments received in response have been made available online.2 The research team revised the study in the light of the comments received and the final version is presented below in the form and language in which it was received by the Secretariat of the Convention on Biological Diversity. -
How Can I Tell If My Algorithm Was Reasonable?
Michigan Technology Law Review Article 2 2021 How Can I Tell if My Algorithm Was Reasonable? Karni A. Chagal-Feferkorn University of Haifa Faculty of Law; University of Ottawa and the University of Ottawa Centre for Law, Technology and Society Follow this and additional works at: https://repository.law.umich.edu/mtlr Part of the Law and Society Commons, Science and Technology Law Commons, and the Torts Commons Recommended Citation Karni A. Chagal-Feferkorn, How Can I Tell if My Algorithm Was Reasonable?, 27 MICH. TECH. L. REV. 213 (2021). Available at: https://repository.law.umich.edu/mtlr/vol27/iss2/2 This Article is brought to you for free and open access by the Journals at University of Michigan Law School Scholarship Repository. It has been accepted for inclusion in Michigan Technology Law Review by an authorized editor of University of Michigan Law School Scholarship Repository. For more information, please contact [email protected]. HOW CAN I TELL IF MY ALGORITHM WAS REASONABLE? Karni A. Chagal-Feferkorn* Abstract Self-learning algorithms are gradually dominating more and more aspects of our lives. They do so by performing tasks and reaching decisions that were once reserved exclusively for human beings. And not only that—in certain contexts, their decision-making performance is shown to be superior to that of humans. However, as superior as they may be, self-learning algorithms (also referred to as artificial intelligence (AI) systems, “smart robots,” or “autonomous machines”) can still cause damage. When determining the liability of a human tortfeasor causing damage, the applicable legal framework is generally that of negligence. -
February Newsletter
Systematic Innovation e-zine Issue 132, March 2013 In this month’s issue: Article – Ten Innovation Trilemmas Article – Holes Not So Funny – Killer Flapjacks Patent of the Month – Temperature Responsive Textiles Best of The Month – Yes To The Mess Conference Report – Hargraves 2013, Sydney Investments – Biological Transistor Generational Cycles – The Wise Prophet Biology – Silver Ant II Short Thort News The Systematic Innovation e-zine is a monthly, subscription only, publication. Each month will feature articles and features aimed at advancing the state of the art in TRIZ and related problem solving methodologies. Our guarantee to the subscriber is that the material featured in the e-zine will not be published elsewhere for a period of at least 6 months after a new issue is released. Readers’ comments and inputs are always welcome. Send them to [email protected] 2013, DLMann, all rights reserved Ten Innovation Trilemmas One day in the not too distant future, we’re hoping to finish the third part in our series on trilemmas. We see the trilemma as the next logical evolution stage to the dilemma (contradiction) story that presently sits at the heart of TRIZ and SI. The basic theory goes something like this: it is relatively easy to resolve a conflict between a pair of system attributes because there is an implied freedom to adversely affect any third attribute that wasn’t part of the problem definition. Solving contradictions helps deliver ‘more ideal’ solutions only in so far as there is an expectation that the two conflicting parameters under consideration are more important than any of the others that might be present in or around the system. -
Synthetic Biology an Overview of the Debates
SYNTHETIC BIOLOGY PROJECT / SYNBIO 3 SYNTHETIC BIOLOGY Ethical Issuesin SYNBIO 3/JUNE2009 An overview ofthedebates Contents Preface 3 Executive Summary 4 Who is doing what, where are they doing it and how is this current work funded? 6 How distinct is synthetic biology from other emerging areas of scientific and technological innovation? 9 Ethics: What harms and benefits are associated with synthetic biology? 12 The pro-actionary and pre-cautionary frameworks 18 N OVERVIEW OF THE DEBATES N OVERVIEW OF A Competing—and potentially complementary—views about non-physical harms (harms to well-being) 23 The most contested harms to well-being 25 Conclusion: Moving the debate forward 26 References 29 ETHICAL ISSUES IN SYNTHETIC BIOLOGY: ETHICAL ISSUES IN SYNTHETIC BIOLOGY: ii The opinions expressed in this report are those of the authors and do not necessarily reflect views Sloan Foundation. Wilson International Center for Scholars or the Alfred P. of the Woodrow Ethical Issues in SYNTHETIC BIOLOGY An overview of the debates Erik Parens, Josephine Johnston, and Jacob Moses The Hastings Center, Garrison, New York SYNBIO 3 / JUNE 2009 2 ETHICAL ISSUES IN SYNTHETIC BIOLOGY: AN OVERVIEW OF THE DEBATES Preface Synthetic biology will allow scientists and where such topics are divided into two broad engineers to create biological systems categories: concerns about physical and non- that do not occur naturally as well as to physical harms. While physical harms often re-engineer existing biological systems to trigger debates about how to proceed among perform novel and beneficial tasks. This researchers, policymakers, and the public, emerging field presents a number of non-physical harms present more difficult opportunities to address ethical issues early conundrums. -
The Biological Microprocessor, Or How to Build a Computer with Biological Parts
Volume No: 7, Issue: 8, April 2013, e201304003, http://dx.doi.org/10.5936/csbj.201304003 CSBJ The biological microprocessor, or how to build a computer with biological parts Gerd HG Moe-Behrens a,* Abstract: Systemics, a revolutionary paradigm shift in scientific thinking, with applications in systems biology, and synthetic biology, have led to the idea of using silicon computers and their engineering principles as a blueprint for the engineering of a similar machine made from biological parts. Here we describe these building blocks and how they can be assembled to a general purpose computer system, a biological microprocessor. Such a system consists of biological parts building an input / output device, an arithmetic logic unit, a control unit, memory, and wires (busses) to interconnect these components. A biocomputer can be used to monitor and control a biological system. Introduction Nature and computers are words that used to mean unrelated Other important contributions to systemics are by the Nobel-prize things. However, this view changed, starting in the 1940s, when a winning work of Ilya Prigogine on self-organization and his systems revolutionary scientific paradigm, systemics based on platonic theory concepts in thermodynamics [10]. Furthermore: Mitchell idealistic philosophy, gained popularity [1] [2] [3]. Feigenbaums work on Chaos theory [11]. Contemporary application The roots of philosophical idealism based systemics goes back to finds systems theory in bioscience in fields such as systems biology, Plato. A centerpiece of Plato’s (428/7 to 348/7 BC) work is his and its practical application synthetic biology [12]. The term systems theory of forms, also called theory of ideas [2]. -
Systems and Control Theoretic Approaches to Engineer Robust
Systems and Control Theoretic Approaches to Engineer Robust Biological Systems by Yili Qian Submitted to the Department of Mechanical Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY September 2020 ○c Massachusetts Institute of Technology 2020. All rights reserved. Author................................................................ Department of Mechanical Engineering August 7, 2020 Certified by. Domitilla Del Vecchio Professor of Mechanical Engineering Thesis Supervisor Accepted by . Nicolas G. Hadjiconstantinou Chairman, Department Committee on Graduate Theses 2 Systems and Control Theoretic Approaches to Engineer Robust Biological Systems by Yili Qian Submitted to the Department of Mechanical Engineering on August 7, 2020, in partial fulfillment of the requirements for the degree of Doctor of Philosophy Abstract Synthetic biology is an emerging field of research aimed to engineer biological systems by inserting programmed DNA molecules into living cells. These DNAs encode the production and subsequent interactions of biomolecules that allow the cells to have novel sensing, computing, and actuation capabilities. However, most success stories to date rely heavily on trial and error. This is mainly because genetic systems are context-dependent: the expression level of a synthetic gene often depends not only on its own regulatory inputs, but also on the expression of other supposedly unconnected genes. This lack of modularity leads to unexpected behaviors when multiple genetic subsystems are composed together, making it difficult to engineer complex systems that function predictably and robustly in practice. This thesis characterizes resource competition as a form of context dependence, and presents control theoretic approaches to engineer robust, context-independent gene networks. -
Synthetic Biology in the United States a Brief History of an Emerging Innovation System
Synthetic Biology in the United States A Brief History of an Emerging Innovation System David Rejeski Global Fellow Wilson Center March 2016 Acknowledgments: I was lucky. I had a front seat during the development of a new field — synthetic biology. Not being a scientist, I had not expected those in the field to open their arms to a foreigner with obvious leanings towards the often maligned and un-scientific field of public policy. But it happened. Dozens of people took the time to talk to me, in person or by phone, about their involvement in the field, their hopes, and their concerns. My special thanks to Paula Olsiewski of the Alfred P. Sloan foundation, who supported the Synthetic Biology Project, myself and my staff, at the Woodrow Wilson Center for eight years. Special thanks also to Drew Endy, who, like a magician pulling rabbits from a hat, seemed to have an endless library of important historical documents and photos he was willing to share. Tom Knight and Peter Carr reviewed early versions of the history section and provided valuable feedback. Thanks to my colleague at the International Institute of Applied Systems Analysis, Leena Ilmola, who integrated me into the proposal for the Finnish Academy, an opportunity I would have certainly missed. This story is my construction and I take responsibility for the interpretation, including any errors or failures of inclusion. Maybe we can make it better. Dave Rejeski Washington, DC The research leading to these results has received funding from the Strategic Research Council at the Academy of Finland under grant agreement no: 293446 - Platform Value Now: Value Capturing in the fast emerging platform ecosystems.