Computational environment for modeling and enhancing community resilience: Introducing the center for risk-based community resilience planning

The resilience of a community is defined as its ability to prepare for, withstand, recover from and adapt to the effects of natural or human-caused disasters, and depends on the performance of the built environment and on supporting social, economic and public institutions that are essential for immediate response and long-term recovery and adaptation. The performance of the built environment generally is governed by codes, standards, and regulations, which are applicable to individual facilities and residences, are based on different performance criteria, and do not account for the interdependence of buildings, transportation, utilities and other infrastructure sectors. The National Institute of Standards and Technology recently awarded a new Center of Excellence (NIST-CoE) for Risk-Based Community Resilience Planning, which is headquartered at Colorado State University and involves nine additional universities. Research in this Center is focusing on three major research thrusts: (1) developing the NIST-Community Resilience Modeling Environment known as NIST-CORE, thereby enabling alternative strategies to enhance community resilience to be measured quantitatively; (2) developing a standardized data ontology, robust data architecture and data management tools in support of NIST-CORE; and (3) performing a comprehensive set of hindcasts on disasters to validate the data architecture and NIST-CORE

A guide to develop community resilience performance goals and assessment metrics for decision making

The National Institute of Standards and Technology (NIST) is conducting outreach and research to develop a Community Resilience Planning Guide for Buildings and Infrastructure Systems and quantitative science-based assessment tools and metrics for community resilience. The research focuses on the performance and rapid recovery of the built environment to a functional level for significant hazard events, and the associated technical and social challenges. Major objectives include the development of a community-level methodology based on performance goals, quantitative science-based resilience assessment tools and metrics based on reliability and risk analysis, and guidance and pre-standard documents that can be adopted by communities and code and standard bodies to support rational public policies for mitigating risk to communities. Science-based decision support tools and metrics are needed to help communities evaluate the performance of built systems that support social and economic functions in a community and assess alternative plans and associated risks. The immediate need for community resilience tools for the built environment is being addressed by NIST through a planning methodology and implementation guidance that includes a process for setting community performance goals and evaluating recovery through time to return of functionality. Quantitative science-based assessment tools and metrics for community resilience, based on reliability and risk principles for integrated ‘system of systems’ modeling, are in early stages of development. Researchers are developing quantitative models of individual infrastructure systems, but much remains to be done before an integrated systems model that incorporates uncertainties in data and system condition is available and validated. The addition of community performance goals, multiple hazard levels, and recovery of functionality to the traditional elements of mitigation, performance and damage levels, and losses and consequences provides a more complete risk-informed assessment of community resilience. NIST outreach and research activities that address these issues are summarized, and a simple risk formulation for resilience that incorporates recovery is proposed.Non UBCUnreviewedThis collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.Othe

Risk-based decision making for sustainable and resilient infrastructure systems

The development of infrastructure systems that are sustainable and resilient is a challenging task that involves a broad range of performance indicators over the system life cycle that affect system functionality and recovery.Peer reviewed: YesNRC publication: Ye

Osakeyhtiön tasekirjapohja: Case: Kouvola Innovation Oy

Kunnan Taitoa Oy:n Kouvolan toimipisteen asiakkaan, Kouvolan kaupungin omistaman yhtiön, Kouvola Innovation Oy:n kirjanpitoa on hoitanut useampi eri henkilö, eikä tilinpäätöstä ja tasekirjaa varten ole ollut valmista pohjaa tai yhtenäistä mallia. Eri vuosien tasekirjoissa on eroja sekä ulkonäössä että sisällössä. Tämän opinnäytetyön tavoitteena oli luoda Kunnan Taitoa Oy:n Kouvolan toimipisteeseen tasekirjapohja vanhoja tasekirjoja kehittämällä. Pohja tulisi Kouvola Innovation Oy:n tilinpäätöksen laatijan apuvälineeksi. Tarkoituksena oli tehdä pohjasta sellainen, että sitä voidaan pienillä muutoksilla hyödyntää muidenkin yhtiöiden tilinpäätökseen ja että se hakee tilinpäätöslaskelmien luvut suoraan konsernikirjanpito-ohjelman tietokannasta. Työssä perehdytään tilinpäätöksen ja tasekirjan sisältöön lainsäädännön, asetuksien, yleisohjeiden ja kirjallisuuden avulla. Teoriaa on kirjoitettu samaan aikaan, kun tasekirjapohjaa on laadittu. Aikaisempia tasekirjoja tutkimalla ja teoriaa selvittämällä pyrittiin löytämään kehittämiskohtia niin ulkoasusta kuin asiasisällöstä. Työn tuloksena on toimiva tasekirjapohja, jota voidaan hyödyntää pienillä muutoksilla muidenkin yhtiöiden, kuin Kouvola Innovation Oy:n tilinpäätökseen. Pohja saatiin rakennettua niin, että se poimii laskelmiin ja liitetietoihin lukuja tietokannasta. Kehittämiskohtia ja niiden ratkaisuja löydettiin sekä niihin liittyviä tarpeellisia jatkotoimenpiteitä.Kouvola Innovation Ltd is a limited liability company owned by City of Kouvola and it is a client of Kunnan Taitoa Ltd, which main line of business is combined office administrative service activities. Different persons have been in charge of accounting at Kouvola Innovation and there has been no ready layout or common pattern for financial statement or balance sheet book. There are differences in appearance and content between annual balance sheet books of different years. The objective of this thesis was to create a new balance sheet book layout for Kunnan Taitoa Ltd’s Kouvola office by improving previous balance sheet books. The layout would be used to assist the making of the financial statement of Kouvola Innovation. The purpose was to create a layout which could be used with small adjustments in financial statements of different companies and which would retrieve numbers of financial statements from group accounting program’s database. The content of financial statement and balance sheet book are discussed in the light of legislation, regulation, guidelines and literature on this thesis. The theory was written simultaneously with the layout compilation. The improvements to appearance and content were aimed to be found by studying previous balance sheet books and theory

Additional file 1: Table S1. of Zoledronic acid alters hematopoiesis and generates breast tumor-suppressive bone marrow cells

Flow cytometry cell-surface markers used to quantify indicated hematopoietic stem and progenitor cell populations. (PDF 16 kb

The interdependent networked community resilience modeling environment (IN-CORE)

In 2015, the U.S National Institute of Standards and Technology (NIST) funded the Center of Excellence for Risk-Based Community Resilience Planning (CoE), a fourteen university-based consortium of almost 100 collaborators, including faculty, students, post-doctoral scholars, and NIST researchers. This paper highlights the scientific theory behind the state-of-the-art cloud platform being developed by the CoE - the Interdisciplinary Networked Community Resilience Modeling Environment (IN-CORE). IN-CORE enables communities, consultants, and researchers to set up complex interdependent models of an entire community consisting of people, businesses, social institutions, buildings, transportation networks, water networks, and electric power networks and to predict their performance and recovery to hazard scenario events, including uncertainty propagation through the chained models. The modeling environment includes a detailed building inventory, hazard scenario models, building and infrastructure damage (fragility) and recovery functions, social science data-driven household and business models, and computable general equilibrium (CGE) models of local economies. An important aspect of IN-CORE is the characterization of uncertainty and its propagation throughout the chained models of the platform.Three illustrative examples of community testbeds are presented that look at hazard impacts and recovery on population, economics, physical services, and social services. An overview of the IN-CORE technology and scientific implementation is described with a focus on four key community stability areas (CSA) that encompass an array of community resilience metrics (CRM) and support community resilience informed decision-making. Each testbed within IN-CORE has been developed by a team of engineers, social scientists, urban planners, and economists. Community models, begin with a community description, i.e., people, businesses, buildings, infrastructure, and progresses to the damage and loss of functions caused by a hazard scenario, i.e., a flood, tornado, hurricane, or earthquake. This process is accomplished through chaining of modular algorithms, as described. The baseline community characteristics and the hazard-induced damage sets are the initial conditions for the recovery models, which have been the least studied area of community resilience but arguably one of the most important. Communities can then test the effect of mitigation and/or policies and compare the effects of “what if” scenarios on physical, social, and economic metrics with the only requirement being that the change much be able to be numerically modeled in IN-CORE