135 research outputs found

    We don’t do Google, we do massive attacks: Notes on creative R&D collaborations

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    The article presents findings from an exploratory study investigating the nature of collaborative research and development in creative industries. Participants in the study are two creative SMEs with extensive experience of participating in collaborative projects. A collective case study approach is adopted with data collected on the factors impinging on the effectiveness of such collaborations. Findings are presented at the macro and micro levels of such collaborations. The paper concludes with a summary of some of the challenges faced by small creative SMEs when collaborating with other organizations during the research and development process

    The Vehicle, Spring 2001

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    Vol. 42, No. 2 Table of Contents To Dream Without CeasingElizabeth Dedmanpage 4-5 Honoring Commandos at Spean BridgeKat Stevenspage 6 The Girl I NamelyKevin Manuspage 7 AbsolutionMike Mauritzenpage 8 Summertime SuperheroesChris Ptasnikpage 9 Flower at GlencoeKat Stevenspage 10 AddictionAdam Funkpage 11 Cornfield in JanuaryRobert Prattepage 12 MelancholyOona Margaret Burkepage 13 In PicturesAmanda McKaypage 14 Words to a Silent FilmBrianne Bolinpage 15 ManagerRobert Prattepage 16 The WellJanet Windegathpage 17 A Meal at the Personal Growth CafeAshley Kieferpage 18 Castlegate Evening at AberdeenKat Stevenspage 19 What We AreKevin Manuspage 20 Ode to My Gin-Soaked OlivesBrianne Bolinpage 21 The Six String PlayerRyan Guimondpage 22 MaxineJay Edwardspage 23 BarefootKrista Bodenpage 24 JulyAdam Funkpage 25 HopeOona Margaret Burkepage 26 UntitledLevy Wooln Dannerpage 27 The One and Only Picture I Have of YouKevin Manuspage 28 Death of a Fat ManBrianne Bolinpage 29-32https://thekeep.eiu.edu/vehicle/1075/thumbnail.jp

    Principles of Robotics: Regulating Robots in the Real World

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    This paper proposes a set of five ethical principles, together with seven high-level messages, as a basis for responsible robotics. The Principles of Robotics were drafted in 2010 and published online in 2011. Since then the principles have influenced, and continue to influence, a number of initiatives in robot ethics but have not, to date, been formally published. This paper remedies that omission

    Plasma lysophosphatidylcholine levels are reduced in obesity and type 2 diabetes

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    BACKGROUND: Obesity and type 2 diabetes (T2DM) are associated with increased circulating free fatty acids and triacylglycerols. However, very little is known about specific molecular lipid species associated with these diseases. In order to gain further insight into this, we performed plasma lipidomic analysis in a rodent model of obesity and insulin resistance as well as in lean, obese and obese individuals with T2DM. METHODOLOGY/PRINCIPAL FINDINGS: Lipidomic analysis using liquid chromatography coupled to mass spectrometry revealed marked changes in the plasma of 12 week high fat fed mice. Although a number of triacylglycerol and diacylglycerol species were elevated along with of a number of sphingolipids, a particularly interesting finding was the high fat diet (HFD)-induced reduction in lysophosphatidylcholine (LPC) levels. As liver, skeletal muscle and adipose tissue play an important role in metabolism, we next determined whether the HFD altered LPCs in these tissues. In contrast to our findings in plasma, only very modest changes in tissue LPCs were noted. To determine when the change in plasma LPCs occurred in response to the HFD, mice were studied after 1, 3 and 6 weeks of HFD. The HFD caused rapid alterations in plasma LPCs with most changes occurring within the first week. Consistent with our rodent model, data from our small human cohort showed a reduction in a number of LPC species in obese and obese individuals with T2DM. Interestingly, no differences were found between the obese otherwise healthy individuals and the obese T2DM patients. CONCLUSION: Irrespective of species, our lipidomic profiling revealed a generalized decrease in circulating LPC species in states of obesity. Moreover, our data indicate that diet and adiposity, rather than insulin resistance or diabetes per se, play an important role in altering the plasma LPC profile

    Computational Systems for Music Improvisation

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    Computational music systems that afford improvised creative interaction in real time are often designed for a specific improviser and performance style. As such the field is diverse, fragmented and lacks a coherent framework. Through analysis of examples in the field we identify key areas of concern in the design of new systems, which we use as categories in the construction of a taxonomy. From our broad overview of the field we select significant examples to analyse in greater depth. This analysis serves to derive principles that may aid designers scaffold their work on existing innovation. We explore successful evaluation techniques from other fields and describe how they may be applied to iterative design processes for improvisational systems. We hope that by developing a more coherent design and evaluation process, we can support the next generation of improvisational music systems

    ADGRL3 (LPHN3) variants predict substance use disorder

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    Genetic factors are strongly implicated in the susceptibility to develop externalizing syndromes such as attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, and substance use disorder (SUD). Variants in the ADGRL3 (LPHN3) gene predispose to ADHD and predict ADHD severity, disruptive behaviors comorbidity, long-term outcome, and response to treatment. In this study, we investigated whether variants within ADGRL3 are associated with SUD, a disorder that is frequently co-morbid with ADHD. Using family-based, case-control, and longitudinal samples from disparate regions of the world (n = 2698), recruited either for clinical, genetic epidemiological or pharmacogenomic studies of ADHD, we assembled recursive-partitioning frameworks (classification tree analyses) with clinical, demographic, and ADGRL3 genetic information to predict SUD susceptibility. Our results indicate that SUD can be efficiently and robustly predicted in ADHD participants. The genetic models used remained highly efficient in predicting SUD in a large sample of individuals with severe SUD from a psychiatric institution that were not ascertained on the basis of ADHD diagnosis, thus identifying ADGRL3 as a risk gene for SUD. Recursive-partitioning analyses revealed that rs4860437 was the predominant predictive variant. This new methodological approach offers novel insights into higher order predictive interactions and offers a unique opportunity for translational application in the clinical assessment of patients at high risk for SUD
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