One-counter Markov decision processes

We study the computational complexity of central analysis problems for One-Counter Markov Decision Processes (OC-MDPs), a class of finitely-presented, countable-state MDPs. OC-MDPs are equivalent to a controlled extension of (discrete-time) Quasi-Birth-Death processes (QBDs), a stochastic model studied heavily in queueing theory and applied probability. They can thus be viewed as a natural ``adversarial'' version of a classic stochastic model. Alternatively, they can also be viewed as a natural probabilistic/controlled extension of classic one-counter automata. OC-MDPs also subsume (as a very restricted special case) a recently studied MDP model called ``solvency games'' that model a risk-averse gambling scenario. Basic computational questions about these models include ``termination'' questions and ``limit'' questions, such as the following: does the controller have a ``strategy'' (or ``policy'') to ensure that the counter (which may for example count the number of jobs in the queue) will hit value 0 (the empty queue) almost surely (a.s.)? Or that it will have infinite limsup value, a.s.? Or, that it will hit value 0 in selected terminal states, a.s.? Or, in case these are not satisfied a.s., compute the maximum (supremum) such probability over all strategies. We provide new upper and lower bounds on the complexity of such problems. For some of them we present a polynomial-time algorithm, whereas for others we show PSPACE- or BH-hardness and give an EXPTIME upper bound. Our upper bounds combine techniques from the theory of MDP reward models, the theory of random walks, and a variety of automata-theoretic methods

Are citations from clinical trials evidence of higher impact research? An analysis of ClinicalTrials.gov

An important way in which medical research can translate into improved health outcomes is by motivating or influencing clinical trials that eventually lead to changes in clinical practice. Citations from clinical trials records to academic research may therefore serve as an early warning of the likely future influence of the cited articles. This paper partially assesses this hypothesis by testing whether prior articles referenced in ClinicalTrials.gov records are more highly cited than average for the publishing journal. The results from four high profile general medical journals support the hypothesis, although there may not be a cause-and effect relationship. Nevertheless, it is reasonable for researchers to use citations to their work from clinical trials records as partial evidence of the possible long-term impact of their research

Is Medical Research Informing Professional Practice More Highly Cited? Evidence from AHFS DI Essentials in Drugs.com

This is an accepted manuscript of an article published by Springer in Scientometrics on 21/02/2017, available online: https://doi.org/10.1007/s11192-017-2292-3 The accepted version of the publication may differ from the final published version.Citation-based indicators are often used to help evaluate the impact of published medical studies, even though the research has the ultimate goal of improving human wellbeing. One direct way of influencing health outcomes is by guiding physicians and other medical professionals about which drugs to prescribe. A high profile source of this guidance is the AHFS DI Essentials product of the American Society of Health-System Pharmacists, which gives systematic information for drug prescribers. AHFS DI Essentials documents, which are also indexed by Drugs.com, include references to academic studies and the referenced work is therefore helping patients by guiding drug prescribing. This article extracts AHFS DI Essentials documents from Drugs.com and assesses whether articles referenced in these information sheets have their value recognised by higher Scopus citation counts. A comparison of mean log-transformed citation counts between articles that are and are not referenced in AHFS DI Essentials shows that AHFS DI Essentials references are more highly cited than average for the publishing journal. This suggests that medical research influencing drug prescribing is more cited than average

Can Microsoft Academic be used for citation analysis of preprint archives? The case of the Social Science Research Network

This is an accepted manuscript of an article published by Springer in Scientometrics on 07/03/2018, available online: https://doi.org/10.1007/s11192-018-2704-z The accepted version of the publication may differ from the final published version.Preprint archives play an important scholarly communication role within some fields. The impact of archives and individual preprints are difficult to analyse because online repositories are not indexed by the Web of Science or Scopus. In response, this article assesses whether the new Microsoft Academic can be used for citation analysis of preprint archives, focusing on the Social Science Research Network (SSRN). Although Microsoft Academic seems to index SSRN comprehensively, it groups a small fraction of SSRN papers into an easily retrievable set that has variations in character over time, making any field normalisation or citation comparisons untrustworthy. A brief parallel analysis of arXiv suggests that similar results would occur for other online repositories. Systematic analyses of preprint archives are nevertheless possible with Microsoft Academic when complete lists of archive publications are available from other sources because of its promising coverage and citation results

Research Blogs and the Discussion of Scholarly Information

The research blog has become a popular mechanism for the quick discussion of scholarly information. However, unlike peer-reviewed journals, the characteristics of this form of scientific discourse are not well understood, for example in terms of the spread of blogger levels of education, gender and institutional affiliations. In this paper we fill this gap by analyzing a sample of blog posts discussing science via an aggregator called ResearchBlogging.org (RB). ResearchBlogging.org aggregates posts based on peer-reviewed research and allows bloggers to cite their sources in a scholarly manner. We studied the bloggers, blog posts and referenced journals of bloggers who posted at least 20 items. We found that RB bloggers show a preference for papers from high-impact journals and blog mostly about research in the life and behavioral sciences. The most frequently referenced journal sources in the sample were: Science, Nature, PNAS and PLoS One. Most of the bloggers in our sample had active Twitter accounts connected with their blogs, and at least 90% of these accounts connect to at least one other RB-related Twitter account. The average RB blogger in our sample is male, either a graduate student or has been awarded a PhD and blogs under his own name

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

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