CRYSTAL AND MOLECULAR-STRUCTURE OF 8,2'-CYCLOADENOSINE TRIHYDRATE

8,2'-Cycloadenosine, C IoHi~NsO4.3H20, is a modified arabinosyladenosine nucleoside which has been cyclized at the C(8) and 0(2') atoms. THe trihydrate crystallizes in the orthorhombic space group P2~2~2~, with a = 8.680 (2), b = 5.991 (2), c = 27.203 (4) A, Z = 4. The structure was refined to R = 0.0672 for 1411 unique reflections, photographically recorded. The arabinofuranose ring has a flattened C(4')-endo-C(3')- exo pucker. The conformation about C(4')-C(5') is gauche-gauche, and that about the sugar-base bond is high anti. The crystal structure involves extensive base-base hydrogen bonding, N(1), N(6) and N(7) all being participants

Experimental Identification of the Kink Instability as a Poloidal Flux Amplification Mechanism for Coaxial Gun Spheromak Formation

The magnetohydrodynamic kink instability is observed and identified experimentally as a poloidal flux amplification mechanism for coaxial gun spheromak formation. Plasmas in this experiment fall into three distinct regimes which depend on the peak gun current to magnetic flux ratio, with (I) low values resulting in a straight plasma column with helical magnetic field, (II) intermediate values leading to kinking of the column axis, and (III) high values leading immediately to a detached plasma. Onset of column kinking agrees quantitatively with the Kruskal-Shafranov limit, and the kink acts as a dynamo which converts toroidal to poloidal flux. Regime II clearly leads to both poloidal flux amplification and the development of a spheromak configuration.Comment: accepted for publication in Physical Review Letter

Speeding up to keep up: exploring the use of AI in the research process.

There is a long history of the science of intelligent machines and its potential to provide scientific insights have been debated since the dawn of AI. In particular, there is renewed interest in the role of AI in research and research policy as an enabler of new methods, processes, management and evaluation which is still relatively under-explored. This empirical paper explores interviews with leading scholars on the potential impact of AI on research practice and culture through deductive, thematic analysis to show the issues affecting academics and universities today. Our interviewees identify positive and negative consequences for research and researchers with respect to collective and individual use. AI is perceived as helpful with respect to information gathering and other narrow tasks, and in support of impact and interdisciplinarity. However, using AI as a way of 'speeding up-to keep up' with bureaucratic and metricised processes, may proliferate negative aspects of academic culture in that the expansion of AI in research should assist and not replace human creativity. Research into the future role of AI in the research process needs to go further to address these challenges, and ask fundamental questions about how AI might assist in providing new tools able to question the values and principles driving institutions and research processes. We argue that to do this an explicit movement of meta-research on the role of AI in research should consider the effects for research and researcher creativity. Anticipatory approaches and engagement of diverse and critical voices at policy level and across disciplines should also be considered

Expert views about missing AI narratives: is there an AI story crisis?

Stories are an important indicator of our vision of the future. In the case of artificial intelligence (AI), dominant stories are polarized between notions of threat and myopic solutionism. The central storytellers-big tech, popular media, and authors of science fiction-represent particular demographics and motivations. Many stories, and storytellers, are missing. This paper details the accounts of missing AI narratives by leading scholars from a range of disciplines interested in AI Futures. Participants focused on the gaps between dominant narratives and the untold stories of the capabilities, issues, and everyday realities of the technology. One participant proposed a "story crisis" in which these narratives compete to shape the public discourse on AI. Our findings indicate that dominant narratives distract and mislead public understandings and conceptions of AI. This suggests a need to pay closer attention to missing AI narratives. It is not simply about telling new stories, it is about listening to existing stories and asking what is wanted from AI. We call for realistic, nuanced, and inclusive stories, working with and for diverse voices, which consider (1) story-teller; (2) genre, and (3) communicative purpose. Such stories can then inspire the next generation of thinkers, technologists, and storytellers

Transmission of hand, foot and mouth disease and its potential driving factors in Hong Kong

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Dynamic optimisation of preventative and corrective maintenance schedules for a large scale urban drainage system

Gully pots or storm drains are located at the side of roads to provide drainage for surface water. We consider gully pot maintenance as a risk-driven maintenance problem. We explore policies for preventative and corrective maintenance actions, and build optimised routes for maintenance vehicles. Our solutions take the risk impact of gully pot failure and its failure behaviour into account, in the presence of factors such as location, season and current status. The aim is to determine a maintenance policy that can automatically adjust its scheduling strategy in line with changes in the local environment, to minimise the surface flooding risk due to clogged gully pots. We introduce a rolling planning strategy, solved by a hyper-heuristic method. Results show the behaviour and strength of the automated adjustment in a range of real-world scenarios