7 research outputs found

    A nexus perspective on competing land demands: wider lessons from a UK policy case study

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    As nations develop policies for low-carbon transitions, conflicts with existing policies and planning tools are leading to competing demands for land and other resources. This raises fundamental questions over how multiple demands can best be managed. Taking the UK as an empirical example, this paper critiques current policies and practices to explore the interdependencies at the water-energy-food nexus. It considers how current land uses and related policies affect the UK’s resilience to climate change, setting out an agenda for research and practice relevant to stakeholders in land-use management, policy and modelling. Despite recent progress in recognising such nexus challenges, most UK land-related policies and associated science continue to be compartmentalised by both scale and sector and seldom acknowledge nexus interconnections. On a temporal level, the absence of an over-arching strategy leaves inter-generational trade-offs poorly considered. Given the system lock-in and the lengthy policy-making process, it is essential to develop alternative ways of providing dynamic, flexible, practical and scientifically robust decision support for policy-makers. A range of ecosystem services need to be valued and integrated into a resilient land-use strategy, including the introduction of non-monetary, physical-unit constraints on the use of particular services

    Interview Guide.

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    <p>Interview Guide.</p

    Sosiaalisen median sisältöstrategia B2B-yritykselle, Case X

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    Tämän opinnäytetyön tavoitteena oli luoda toimeksiantajayritykselle sosiaalisen median sisältöstrategia, jonka avulla voidaan lisätä yrityksen näkyvyyttä nykyisten ja potentiaalisten yritysasiakkaiden keskuudessa. Strategiaa varten tavoitteena oli selvittää, missä kanavissa ja minkälaista sisältöä toimeksiantajayrityksen olisi kannattavaa julkaista. Tutkimus oli toimeksiantajayritykselle ajankohtainen ja teoreettisen viitekehyksen avulla pyrittiin tuomaan myös toimeksiantajayritykselle tietoa käsiteltävistä aiheista. Opinnäytetyön teoreettisessa viitekehyksessä käsiteltiin inbound-markkinointia, sisältömarkkinointia ja sosiaalista mediaa B2B-markkinoinnissa. Tämä opinnäytetyö oli toiminnallinen opinnäytetyö. Teoriaosassa kerättyä tietoa täydennettiin benchmarking-tutkimuksella, joka toteutettiin samalla toimialalla toimiville yrityksille. Tutkimuksen kohteina olivat julkaisukanavat, sisältöjen aiheet ja erot eri kanavien välillä sekä sisältöjen välitysmuoto. Myös seuraajamääriin kiinnitettiin huomiota tutkimuksessa. Tutkimus suoritettiin Facebookissa, Twitterissä ja LinkedInissä. Tämän opinnäytetyön lopputuloksena syntyi sosiaalisen median sisältöstrategia toimeksiantajayritykselle. Toimeksiantajayritys oli tyytyväinen lopputulokseen ja opinnäytetyön tavoitteet saavutettiin. Toimeksiantajayritys sai myös opinnäytetyön avulla teoreettista tietoa inbound-markkinoinnista, sisältömarkkinoinnista ja sosiaalisen median hyödyntämisestä B2B-markkinoinnissa.The purpose of this thesis was to create a social media content strategy for the case company for increasing the visibility of the case company among its business customers and potential business customers. The aim of the study was to find out which social media channels and what kind of content the case company should publish. Theoretical framework included information about inbound-marketing, content marketing and utilization of social media in B2B-marketing. This thesis was an operational thesis and the information gathered in theoretical part of the study was completed with a benchmarking research made of five companies in the same field of business as the case company. The subjects of the research were the social media channels used, themes and differences of contents in different channels and the forms of content. The number of followers in companies’ social media channels were examined too. The research was implemented in Facebook, Twitter and LinkedIn, The result of this thesis was a social media content strategy for the case company. The company liked the results and the targets were reached. The study was current for the case company and the case company got theoretical knowledge of inbound-marketing, content marketing and about using the social media in B2B-marketing

    Schematic representation of the genetic environment of the <i>bla</i><sub>NDM-1</sub> common region and gene duplication organization in ST14 isolates CFSAN044566 and CFSAN044568.

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    <p><i>bla</i><sub>NDM-1</sub> is in red, other genes in blue, duplicated copies in green, and insertion sequences are in light blue. The <i>bla</i><sub>NDM-1</sub> common region includes a truncated ISaba125, the <i>bla</i><sub>NDM-1</sub> gene, the bleomycin resistance protein (<i>ble</i><sub>MBL</sub>) and phosphoribosylanthranilate isomerase (<i>trpF</i>) genes. Duplicate copies of four genes (<i>bla</i><sub>OXA-10</sub>, <i>aadA1</i>, <i>qacEdelta1</i>, and <i>sul1</i>) were found. The <i>tat</i> gene is present in two copies split in the middle in one instance. A straight line indicates gaps between the ORFs.</p

    Cladogram of the Kmer distance tree derived from the NCBI Pathogen Detection database comprising 5169 <i>Klebsiella pneumoniae</i> isolates at time of writing.

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    <p>The tree also shows MLST, <i>wzi</i> typing, and the presence of <i>bla</i><sub>OXA-48</sub> and <i>bla</i><sub>NDM-1</sub> genes for the 10 clinical isolates and sequence control strain (ATCC 43816), as well as their closest relatives. For space optimization, all other isolates were collapsed into straight lines comprising different numbers (aka leaves). Colistin susceptibility is indicated with different colored dots: green (susceptible); red (resistant); and white (no information). The identification for the BioSample and SNP cluster (when available) is also provided. The complete tree file from NCBI Pathogen detection (PDG000000012.284.reference_target.tree.asn—as of March 24th, 2018), can be downloaded at <a href="https://doi.org/10.6084/m9.figshare.5708347.v2" target="_blank">https://doi.org/10.6084/m9.figshare.5708347.v2</a> and can be opened with NCBI software Genome Workbench (<a href="https://www.ncbi.nlm.nih.gov/tools/gbench/" target="_blank">https://www.ncbi.nlm.nih.gov/tools/gbench/</a>). Given that the kmer tree only includes a reference isolate from each SNP clusters plus singleton isolates, CFSAN044573 (marked in gray) is not included in the original tree but it is listed here for completeness of information.</p
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