The U.S. Department of Defense originally designed the Internet to increase the productivity of government workers and it has now become an enormous opportunity for businesses to advertise, correspond with clients, order from suppliers, and conduct many other business functions at minimal cost. The Internet has achieved faster acceptance by Americans than any other previous technologies and businesses are already discovering that the Web is having a profound impact on how they conduct business. Conservative estimates are for Internet retail sales to reach $7 billion by the year 2000, and some respected analysts predict it to grow to $100 billion over the next five to eight years. As with any new initiative, there are costs, benefits, and risks associated with the undertaking. Anyone who wishes to maintain a Web site on the Internet can do so at a modest cost, or in some cases at no cost. One of the many benefits to be gained from placing a company on the Internet such as gaining access to the World Wide Web (WWW). The WWW gives anyone who is connected the ability to communicate with distant computers all over the world and provides the benefit of being able to send and receive electronic mail (E-mail). While there are a number of different risks incurred when a company establishes a Web site and goes on the Internet the biggest concern, by far, is security. When a company installs a Web server at their site, they open a window into their local network that the entire Internet can peer through. These substantial risks notwithstanding, the Internet provides an opportunity that business cannot afford to pass up. The number of companies that have already taken advantage of the Internet and the rapid increase in the number of Internet users has fueled a phenomenal growth in electronic commerce. The Internet provides an excellent opportunity to increase sales at a lower marginal cost than was possible before. Companies that pass up this tremendous opportunity will probably not survive in the 21st century competitive climate.
This paper tells the story of how a group of academic staff and students set out to establish a subversive teaching and learning project: Student as Producer, across an English university. Confronted by the intensification of neoliberal education policies and faced with the recuperation of its radical practice, the paper recounts how staff and students involved with Student as Producer moved outside of the university in 2011 to set up a cooperative form of higher education: the Social Science Centre, Lincoln, where students can attain higher education awards without the burden of debt, along with the experience of running a workers' cooperative. This subversive practice is grounded in a Marxist 'critique of value', underpinned by a politics of abolition based on the work of Thomas Mathiesen. The paper concludes that it is possible and necessary to create new dissident institutions 'in and against' the organisational forms of capitalist society as the embodiment of revolutionary theory.
The wellbeing of prison governors has received little attention in penological research to date. The findings of this research reveal that governors' wellbeing is negatively impacted by a dominant Masculinity Contest Culture (MCC) permeating through the organisation. While MCC negatively contributes to governors' wellbeing, they continue to engage in hegemonic masculine performances to show no weakness to cope with the pressures of working life. This has led to the emergence of a 'hyper-MCC' which we define as an overperformance of the MCC social script that is seen as a requirement to cope within an increasingly challenging workplace. The implications of hyper-MCC are a perpetuation of a toxic working culture and a reduced likelihood of engaging with wellbeing services. The response needs to be developing the right types of support that can attempt to re-frame dominant masculine working cultures, challenge hyper-MCC performances and remove the individualised responsibility of wellbeing away from the workforce themselves. However, this cultural shift will only be effective if coupled with a meaningful reconsideration of working conditions, which have resulted in the intensification of workloads and practices.
Beacon is a basic data discovery protocol issued by the Global Alliance for Genomics and Health (GA4GH). The main goal addressed by version 1 of the Beacon protocol was to test the feasibility of broadly sharing human genomic data, through providing simple "yes" or "no" responses to queries about the presence of a given variant in datasets hosted by Beacon providers. The popularity of this concept has fostered the design of a version 2, that better serves real-world requirements and addresses the needs of clinical genomics research and healthcare, as assessed by several contributing projects and organizations. Particularly, rare disease genetics and cancer research will benefit from new case level and genomic variant level requests and the enabling of richer phenotype and clinical queries as well as support for fuzzy searches. Beacon is designed as a "lingua franca" to bridge data collections hosted in software solutions with different and rich interfaces. Beacon version 2 works alongside popular standards like Phenopackets, OMOP, or FHIR, allowing implementing consortia to return matches in beacon responses and provide a handover to their preferred data exchange format. The protocol is being explored by other research domains and is being tested in several international projects. ; This study was funded by ELIXIR, the research infrastructure for life-science data and also by LaCaixa Foundation (grant number 004745/008034). Tim Beck was supported by a UKRI Innovation Fellowship at Health Data Research UK (MR/S003703/1). Anthony J. Brookes and Jordi Rambla were supported, in part, by the European Union's Horizon 2020 research and innovation program under the EJP RD COFUND-EJP #825575. Michael Baudis acknowledges funding under the BioMedIT Network project of Swiss Institute of Bioinformatics (SIB) and Swiss Personalized Health Network (SPHN). ; Peer reviewed
Glacial vicariance is regarded as one of the most prevalent drivers of phylogeographic structure and speciation among high-latitude organisms, but direct links between ice advances and range fragmentation have been more difficult to establish in marine than in terrestrial systems. Here we investigate the evolution of largely disjunct (and potentially reproductively isolated) phylogeographic lineages within the amphi-boreal kelp Saccharina latissima s.l. Using molecular data (COI, microsatellites) we confirm that S. latissima comprises also the NE Pacific S. cichorioides complex and is composed of divergent lineages with limited range overlap and genetic admixture. Only a few genetic hybrids were detected throughout a Canadian Arctic/NW Greenland contact zone. The degree of genetic differentiation and sympatric isolation of phylogroups suggest that S. latissima s.l. represents a complex of incipient species. Phylogroup distributions compared with paleo-environmental reconstructions of the cryosphere further suggest that diversification within S. latissima results from chronic glacial isolation in disjunct persistence areas intercalated with ephemeral interglacial poleward expansions and admixture at high-latitude (Arctic) contact zones. This study thus supports a role for glaciations not just in redistributing pre-existing marine lineages but also as a speciation pump across multi-glacial cycles for marine organisms otherwise exhibiting cosmopolite amphi-boreal distributions. ; Pew Foundation (USA); Portuguese FCT (Fundacao para a Ciencia e a Tecnologia) through program GENEKELP [PTDC/MAR-EST/6053/2014]; Portuguese FCT (Fundacao para a Ciencia e a Tecnologia) through program MARFOR [Biodiversa/0004/2015]; Portuguese FCT (Fundacao para a Ciencia e a Tecnologia) [UID/Multi/04326/2013, SFRH/BPD/88935/2012, SFRH/BPD/111003/2015]; NSERC; FRQNT; Canada Foundation for Innovation; New Brunswick Innovation Foundation; European Union's Seventh Framework Programme [226248]; Danish Environmental Protection Agency within the ...
Beacon is a basic data discovery protocol issued by the Global Alliance for Genomics and Health (GA4GH). The main goal addressed by version 1 of the Beacon protocol was to test the feasibility of broadly sharing human genomic data, through providing simple "yes" or "no" responses to queries about the presence of a given variant in datasets hosted by Beacon providers. The popularity of this concept has fostered the design of a version 2, that better serves real-world requirements and addresses the needs of clinical genomics research and healthcare, as assessed by several contributing projects and organizations. Particularly, rare disease genetics and cancer research will benefit from new case level and genomic variant level requests and the enabling of richer phenotype and clinical queries as well as support for fuzzy searches. Beacon is designed as a "lingua franca" to bridge data collections hosted in software solutions with different and rich interfaces. Beacon version 2 works alongside popular standards like Phenopackets, OMOP, or FHIR, allowing implementing consortia to return matches in beacon responses and provide a handover to their preferred data exchange format. The protocol is being explored by other research domains and is being tested in several international projects. ; This study was funded by ELIXIR, the research infrastructure for lifescience data and also by La Caixa Foundation (grant number 004745/ 008034). Tim Beck was supported by a UKRI Innovation Fellowship at Health Data Research UK (MR/S003703/1). Anthony J. Brookes and Jordi Rambla were supported, in part, by the European Union's Horizon 2020 research and innovation program under the EJP RD COFUND‐EJP #825575. Michael Baudis acknowledges funding under the BioMedIT Network project of Swiss Institute of Bioinformatics (SIB) and Swiss Personalized Health Network (SPHN)
ELIXIR's International Strategy describes current activities of international relevance, and planned implementation actions to reinforce ELIXIR's global significance and impact. An update is released on an annual basis. In the context of this document, the term 'International' means 'beyond Europe', with 'Europe' defined as the countries of the European Research Area1 (ERA). The Strategy is articulated around four main objectives: (1) scale-up the international user base of ELIXIR's Services, (2) improve bioinformatics services and promote global standards, (3) expand Membership in ELIXIR beyond Europe, and (4) ensure that ELIXIR is recognised as an infrastructure of global relevance, and a partner of choice by intergovernmental organisations. The international audience of the Strategy encompasses users of bioinformatics services, national-level bioinformatics infrastructures, and government officials in Ministries. Also targeted by this Strategy are international bioinformatics-related initiatives and organisations, and intergovernmental organisations. Closer to home, the Strategy aims to raise awareness of ELIXIR's global significance within Member countries, and guide efforts to ensure coherent implementation actions in support of the objectives of the Strategy. The strategy will be implemented through a concrete set of Actions, described in Annex I, each relating to one of the four specific Objectives.
The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits. ; B.P.C. acknowledges funding from Abigail Wexner Research Institute at Nationwide Children's Hospital; T.H. Nyrönen acknowledges funding from Academy of Finland grant #31996; A.M.-J., K.N., T.F.B., O.M.H., and Z.S. acknowledge funding from Australian Medical Research Future Fund; M.S. acknowledges funding from Biobank Japan; D. Bujold and S.J.M.J. acknowledge funding from Canada Foundation for Innovation; L.J.D. acknowledges funding from Canada Foundation for Innovation Cyber Infrastructure grant #34860; D. Bujold and G.B. acknowledge funding from CANARIE; L.J.D. acknowledges funding from CANARIE Research Data Management contract #RDM-090 (CHORD) and #RDM2-053 (ClinDIG); K.K.-L. acknowledges funding from CanSHARE; T.L.T. acknowledges funding from Chan Zuckerberg Initiative; T. Burdett acknowledges funding from Chan Zuckerberg Initiative grant #2017-171671; D. Bujold, G.B., and L.D.S. acknowledge funding from CIHR; L.J.D. acknowledges funding from CIHR grant #404896; M.J.S.B. acknowledges funding from CIHR grant #SBD-163124; M. Courtot and M. Linden acknowledge funding from CINECA project EU Horizon 2020 grant #825775; D. Bujold and G.B. acknowledge funding from Compute Canada; F.M.-G. acknowledges funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – NFDI 1/1 "GHGA – German Human Genome-Phenome Archive; R.M.H.-S. acknowledges funding from Duke-Margolis Center for Health Policy; S.B. and A.J.B. acknowledge funding from EJP-RD EU Horizon 2020 grant #825575; A. Niewielska, A.K., D.S., G.I.S., J.A.T., J.R., M.A.K., M. Baudis, M. Linden, S.B., S.S., T.H. Nyrönen, and T.M.K. acknowledge funding from ELIXIR; A. Niewielska acknowledges funding from EOSC-Life EU Horizon 2020 grant #824087; J.-P.H. acknowledges funding from ETH Domain Strategic Focal Area "Personalized Health and Related Technologies (PHRT)" grant #2017-201; F.M.-G. acknowledges funding from EUCANCan EU Horizon 2020 grant #825835; B.M.K., D. Bujold, G.B., L.D.S., M.J.S.B., N.S., S.E.W., and Y.J. acknowledge funding from Genome Canada; B.M.K., M.J.S.B., S.E.W., and Y.J. acknowledge funding from Genome Quebec; F.M.-G. acknowledges funding from German Human Genome-Phenome Archive; C. Voisin acknowledges funding from Google; A.J.B. acknowledges funding from Health Data Research UK Substantive Site Award; D.H. acknowledges funding from Howard Hughes Medical Institute; S.B. acknowledges funding from Instituto de Salud Carlos III; S.-S.K. and K.T. acknowledge funding from Japan Agency for Medical Research and Development (AMED); S. Ogishima acknowledges funding from Japan Agency for Medical Research and Development (AMED) grant #20kk0205014h0005; C.Y. and K. Kosaki acknowledge funding from Japan Agency for Medical Research and Development (AMED) grant #JP18kk0205012; GEM Japan acknowledges funding from Japan Agency for Medical Research and Development (AMED) grants #19kk0205014h0004, #20kk0205014h0005, #20kk0205013h0005, #20kk0205012h0005, #20km0405401h0003, and #19km0405001h0104; J.R. acknowledges funding from La Caixa Foundation under project #LCF/PR/GN13/50260009; R.R.F. acknowledges funding from Mayo Clinic Center for Individualized Medicine; Y.J. and S.E.W. acknowledge funding from Ministère de l'Économie et de l'Innovation du Québec for the Can-SHARE Connect Project; S.E.W. and S.O.M.D. acknowledge funding from Ministère de l'Économie et de l'Innovation du Québec for the Can-SHARE grant #141210; M.A.H., M.C.M.-T., J.O.J., H.E.P., and P.N.R. acknowledge funding from Monarch Initiative grant #R24OD011883 and Phenomics First NHGRI grant #1RM1HG010860; A.L.M. and E.B. acknowledge funding from MRC grant #MC_PC_19024; P.T. acknowledges funding from National University of Singapore and Agency for Science, Technology and Research; J.M.C. acknowledges funding from NHGRI; A.H.W. acknowledges funding from NHGRI awards K99HG010157, R00HG010157, and R35HG011949; A.M.-J., K.N., D.P.H., O.M.H., T.F.B., and Z.S. acknowledge funding from NHMRC grants #GNT1113531 and #GNT2000001; D.L.C. acknowledges funding from NHMRC Ideas grant #1188098; A.B.S. acknowledges funding from NHMRC Investigator Fellowship grant #APP177524; J.M.C. and L.D.S. acknowledge funding from NIH; A.A.P. acknowledges funding from NIH Anvil; A.V.S. acknowledges funding from NIH contract #HHSN268201800002I (TOPMed Informatics Research Center); S.U. acknowledges funding from NIH ENCODE grant #UM1HG009443; M.C.M.-T. and M.A.H. acknowledge funding from NIH grant #1U13CA221044; R.J.C. acknowledges funding from NIH grants #1U24HG010262 and #1U2COD023196; M.G. acknowledges funding from NIH grant #R00HG007940; J.B.A., S.L., P.G., E.B., H.L.R., and L.S. acknowledge funding from NIH grant #U24HG011025; K.P.E. acknowledges funding from NIH grant #U2C-RM-160010; J.A.E. acknowledges funding from NIH NCATS grant #U24TR002306; M.M. acknowledges funding from NIH NCI contract #HHSN261201400008c and ID/IQ Agreement #17X146 under contract #HHSN2612015000031 and #75N91019D00024; R.M.C.-D. acknowledges funding from NIH NCI grant #R01CA237118; M. Cline acknowledges funding from NIH NCI grant #U01CA242954; K.P.E. acknowledges funding from NIH NCI ITCR grant #1U24CA231877-01; O.L.G. acknowledges funding from NIH NCI ITCR grant #U24CA237719; R.L.G. acknowledges funding from NIH NCI task order #17X147F10 under contract #HHSN261200800001E; A.F.R. acknowledges funding from NIH NHGRI grant #RM1HG010461; N.M. and L.J.Z. acknowledge funding from NIH NHGRI grant #U24HG006941; R.R.F., T.H. Nelson, L.J.B., and H.L.R. acknowledge funding from NIH NHGRI grant #U41HG006834; B.J.W. acknowledges funding from NIH NHGRI grant #UM1HG009443A; M. Cline acknowledges funding from NIH NHLBI BioData Catalyst Fellowship grant #5118777; M.M. acknowledges funding from NIH NHLBI BioData Catalyst Program grant #1OT3HL142478-01; N.C.S. acknowledges funding from NIH NIGMS grant #R35-GM128636; M.C.M.-T., M.A.H., P.N.R., and R.R.F. acknowledge funding from NIH NLM contract #75N97019P00280; E.B. and A.L.M. acknowledge funding from NIHR; R.G. acknowledges funding from Project Ris3CAT VEIS; S.B. acknowledges funding from RD-Connect, Seventh Framework Program grant #305444; J.K. acknowledges funding from Robertson Foundation; S.B. and A.J.B. acknowledge funding from Solve-RD, EU Horizon 2020 grant #779257; T.S. and S. Oesterle acknowledge funding from Swiss Institute of Bioinformatics (SIB) and Swiss Personalized Health Network (SPHN), supported by the Swiss State Secretariat for Education, Research and Innovation SERI; S.J.M.J. acknowledges funding from Terry Fox Research Institute; A.E.H., M.P.B., M. Cupak, M.F., and J.F. acknowledge funding from the Digital Technology Supercluster; D.F.V. acknowledges funding from the Australian Medical Research Future Fund, as part of the Genomics Health Futures Mission grant #76749; M. Baudis acknowledges funding from the BioMedIT Network project of Swiss Institute of Bioinformatics (SIB) and Swiss Personalized Health Network (SPHN); B.M.K. acknowledges funding from the Canada Research Chair in Law and Medicine and CIHR grant #SBD-163124; D.S., G.I.S., M.A.K., S.B., S.S., and T.H. Nyrönen acknowledge funding from the EU Horizon 2020 Beyond 1 Million Genomes (B1MG) Project grant #951724; P.F., A.D.Y., F.C., H.S., I.U.L., D. Gupta, M. Courtot, S.E.H., T. Burdett, T.M.K., and S.F. acknowledge funding from the European Molecular Biology Laboratory; Y.J. and S.E.W. acknowledge funding from the Government of Canada; P.G. acknowledges funding from the Government of Canada through Genome Canada and the Ontario Genomics Institute (OGI-206); J.Z. acknowledges funding from the Government of Ontario; C.K.Y. acknowledges funding from the Government of Ontario, Canada Foundation for Innovation; C. Viner and M.M.H. acknowledge funding from the Natural Sciences and Engineering Research Council of Canada (grant #RGPIN-2015-03948 to M.M.H. and Alexander Graham Bell Canada Graduate Scholarship to C.V.); K.K.-L. acknowledges funding from the Program for Integrated Database of Clinical and Genomic Information; J.K. acknowledges funding from the Robertson Foundation; D.F.V. acknowledges funding from the Victorian State Government through the Operational Infrastructure Support (OIS) Program; A.M.L., R.N., and H.V.F. acknowledge funding from Wellcome (collaborative award); F.C., H.S., P.F., and S.E.H. acknowledge funding from Wellcome Trust grant #108749/Z/15/Z; A.D.Y., H.S., I.U.L., M. Courtot, H.E.P., P.F., and T.M.K. acknowledge funding from Wellcome Trust grant #201535/Z/16/Z; A.M., J.K.B., R.J.M., R.M.D., and T.M.K. acknowledge funding from Wellcome Trust grant #206194; E.B., P.F., P.G., and S.F. acknowledge funding from Wellcome Trust grant #220544/Z/20/Z; A. Hamosh acknowledges funding from NIH NHGRI grant U41HG006627 and U54HG006542; J.S.H. acknowledges funding from National Taiwan University #91F701-45C and #109T098-02; the work of K.W.R. was supported by the Intramural Research Program of the National Library of Medicine, NIH. For the purpose of open access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. H.V.F. acknowledges funding from Wellcome Grant 200990/A/16/Z 'Designing, developing and delivering integrated foundations for genomic medicine'. ; Peer reviewed