Aspects of Discrete Breathers and New Directions

We describe results concerning the existence proofs of Discrete Breathers (DBs) in the two classes of dynamical systems with optical linear phonons and with acoustic linear phonons. A standard approach is by continuation of DBs from an anticontinuous limit. A new approach, which is purely variational, is presented. We also review some numerical results on intraband DBs in random nonlinear systems. Some non-conventional physical applications of DBs are suggested. One of them is understanding slow relaxation properties of glassy materials. Another one concerns energy focusing and transport in biomolecules by targeted energy transfer of DBs. A similar theory could be used for describing targeted charge transfer of nonlinear electrons (polarons) and, more generally, for targeted transfer of several excitations (e.g. Davydov soliton).Comment: to appear in the Proceedings of NATO Advanced Research Workshop "Nonlinearity and Disorder: Theory and Applications", Tashkent,Uzbekistan,October 1-6, 200

Evaluation of QuitNow Men: An Online, Men-Centered Smoking Cessation Intervention.

BACKGROUND: Men continue to smoke cigarettes in greater numbers than women. There is growing evidence for the value of developing targeted, men-centered health promotion programs. However, few smoking cessation interventions have been designed for men. A gender-specific website, QuitNow Men, was developed based on focus group interview findings, stakeholder feedback, and evidence-based cessation strategies. The website was designed to incorporate a masculine look and feel through the use of images, direct language, and interactive content. Usability experts and end-users provided feedback on navigation and functionality of the website prior to pilot testing. OBJECTIVES: The objectives of the pilot study were to describe (1) men's use and evaluations of the interactive resources and information on the QuitNow Men website, and (2) the potential of QuitNow Men to engage men in reducing and quitting smoking. METHODS: A one-group, pretest-posttest study design was used. Men who were interested in quitting were recruited and invited to use the website over a 6-month period. Data were collected via online questionnaires at baseline, 3-month, and 6-month follow-up. A total of 117 men completed the baseline survey. Over half of those (67/117, 57.3%) completed both follow-up surveys. RESULTS: At baseline, participants (N=117) had been smoking for an average of 24 years (SD 12.1) and smoked on average 15 cigarettes a day (SD 7.4). The majority had not previously used a quit smoking website (103/117, 88.0%) or websites focused on men's health (105/117, 89.7%). At the 6-month follow-up, the majority of men used the QuitNow Men website at least once (64/67, 96%). Among the 64 users, 29 (43%) reported using the website more than 6 times. The men using QuitNow Men agreed or strongly agreed that the website was easy to use (51/64, 80%), the design and images were appealing (42/64, 66%), they intended to continue to use the website (42/64, 66%), and that they would recommend QuitNow Men to others who wanted to quit (46/64, 72%). Participants reported using an average of 8.76 (SD 4.08) of the 15 resources available on the website. At 6-month follow-up, 16 of the 67 participants (24%) had quit, 27 (40%) had reduced their smoking and 24 (36%) had not changed their smoking habits. Repeated measures general linear model showed a significant decrease in the number of cigarettes smoked between the 3-month and 6-month follow-up (F1,63=6.41, P=.01, eta squared=0.09). Number of resources used on the website, quit confidence, nicotine dependence and age significantly predicted number of quit attempts by those still smoking at 6 months (F4,45=2.73, P=.04), with number of resources used being the strongest predictor (P=.02). CONCLUSIONS: The results of this research support efforts to integrate gender-sensitive approaches in smoking cessation interventions and indicate that this novel Web-based resource has potential in supporting men's smoking cessation efforts

Bayesian system identification of MDOF nonlinear systems using highly informative training data

The aim of this paper is to utilise the concept of “highly informative training data” such that, using Markov chain Monte Carlo (MCMC) methods, one can apply Bayesian system identification to multi-degree-of-freedom nonlinear systems with relatively little computational cost. Specifically, the Shannon entropy is used as a measure of information content such that, by analysing the information content of the posterior parameter distribution, one is able to select and utilise a relatively small but highly informative set of training data (thus reducing the cost of running MCMC)

Improved genome editing in human cell lines using the CRISPR method

The Cas9/CRISPR system has become a popular choice for genome editing. In this system, binding of a single guide (sg) RNA to a cognate genomic sequence enables the Cas9 nuclease to induce a double-strand break at that locus. This break is next repaired by an error-prone mechanism, leading to mutation and gene disruption. In this study we describe a range of refinements of the method, including stable cell lines expressing Cas9, and a PCR based protocol for the generation of the sgRNA. We also describe a simple methodology that allows both elimination of Cas9 from cells after gene disruption and re-introduction of the disrupted gene. This advance enables easy assessment of the off target effects associated with gene disruption, as well as phenotype-based structure-function analysis. In our study, we used the Fan1 DNA repair gene as control in these experiments. Cas9/CRISPR-mediated Fan1 disruption occurred at frequencies of around 29%, and resulted in the anticipated spectrum of genotoxin hypersensitivity, which was rescued by re-introduction of Fan1

Hamlet and the fall of the Berlin wall : the myth of interventionist Shakespeare performance

The critical reception of Heiner Müller’s 1990 Hamlet/Maschine at the Deutsches Theater in East Berlin epitomizes a trend of crediting GDR Shakespeare performance with political influence. Drawing on rehearsal notes and reviews, Oliver challenges the interventionist Shakespeare myth, contrasting the Deutsches Theater’s political involvement with the impact of its Hamlet production on events surrounding the fall of the Berlin Wall. Shakespeare’s capacity for political intervention at this point was limited by theater practitioners’ reliance on public funding, their close relationships with governmental authority, and an underlying distrust of the masses. Ultimately, GDR artists proved useful to the 1989 protest movement because they occupied a unique position at the interface of dissidence and power

Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. This property is shared with other complex sequential behaviors. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model (GMM)), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex sequences with higher-order dependencies