Random qubit-states and how best to measure them

We consider the problem of measuring a single qubit, known to have been prepared in either a randomly selected pure state or a randomly selected real pure state. We seek the measurements that provide either the best estimate of the state prepared or maximise the accessible information. Surprisingly, any sensible measurement turns out to be optimal. We discuss the application of these ideas to multiple qubits and higher-dimensional systems

Autoregressive clustering for HMM speech synthesis

The autoregressive HMM has been shown to provide efficient parameter estimation and high-quality synthesis, but in previous experiments decision trees derived from a non-autoregressive system were used. In this paper we investigate the use of autoregressive clustering for autoregressive HMM-based speech synthesis. We describe decision tree clustering for the autoregressive HMM and highlight differences to the standard clustering procedure. Subjective listening evaluation results suggest that autoregressive clustering improves the naturalness of the resulting speech. We find that the standard minimum description length (MDL) criterion for selecting model complexity is inappropriate for the autoregressive HMM. Investigating the effect of model complexity on naturalness, we find that a large degree of overfitting is tolerated without a substantial decrease in naturalness.This research was funded by the European Community's Seventh Framework Programme (FP7/2007-2013), grant agreement 213845 (EMIME)

Autoregressive HMMs for speech synthesis

We propose the autoregressive HMM for speech synthesis. We show that the autoregressive HMM supports efficient EM parameter estimation and that we can use established effective synthesis techniques such as synthesis considering global variance with minimal modification. The autoregressive HMM uses the same model for parameter estimation and synthesis in a consistent way, in contrast to the standard HMM synthesis framework, and supports easy and efficient parameter estimation, in contrast to the trajectory HMM. We find that the autoregressive HMM gives performance comparable to the standard HMM synthesis framework on a Blizzard Challenge-style naturalness evaluation.This research was funded by the European Community's Seventh Framework Programme (FP7/2007-2013), grant agreement 213845 (EMIME)

Antidepressant Activity of Pharmacological and Genetic Deactivation of the Small-Conductance Calcium-Activated Potassium Channel Subtype-3

Funding and Disclosure This research was supported by awards from the Neuroscience Catalyst program (Toronto) (FRB and JNN), the Canadian Institutes of Health Research (FRB and JN) and the National Science and Engineering Research Council of Canada (FRB). M.N. was additionally supported by a CAMH Discovery Fund Post-doctoral Fellowship. Conflict of Interest: None declared. Acknowledgments We thank J. Li, U. Mumtaz, S. Khan, S. Sivaruban, M. Billyard, E. Hauck, D. Oleinichenko, Michael Coombs and Lucas Francis Fowler for technical assistance at different stages of the work.Peer reviewedPostprin

Lactate signalling regulates fungal β-glucan masking and immune evasion

AJPB: This work was supported by the European Research Council (STRIFE, ERC- 2009-AdG-249793), The UK Medical Research Council (MR/M026663/1), the UK Biotechnology and Biological Research Council (BB/K017365/1), the Wellcome Trust (080088; 097377). ERB: This work was supported by the UK Biotechnology and Biological Research Council (BB/M014525/1). GMA: Supported by the CNPq-Brazil (Science without Borders fellowship 202976/2014-9). GDB: Wellcome Trust (102705). CAM: This work was supported by the UK Medical Research Council (G0400284). DMM: This work was supported by UK National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC/K000306/1). NARG/JW: Wellcome Trust (086827, 075470,101873) and Wellcome Trust Strategic Award in Medical Mycology and Fungal Immunology (097377). ALL: This work was supported by the MRC Centre for Medical Mycology and the University of Aberdeen (MR/N006364/1).Peer reviewedPostprin

Intuitive Visualization and Analysis of Multi-Omics Data and Application to Escherichia coli Carbon Metabolism

Combinations of ‘omics’ investigations (i.e, transcriptomic, proteomic, metabolomic and/or fluxomic) are increasingly applied to get comprehensive understanding of biological systems. Because the latter are organized as complex networks of molecular and functional interactions, the intuitive interpretation of multi-omics datasets is difficult. Here we describe a simple strategy to visualize and analyze multi-omics data. Graphical representations of complex biological networks can be generated using Cytoscape where all molecular and functional components could be explicitly represented using a set of dedicated symbols. This representation can be used i) to compile all biologically-relevant information regarding the network through web link association, and ii) to map the network components with multi-omics data. A Cytoscape plugin was developed to increase the possibilities of both multi-omic data representation and interpretation. This plugin allowed different adjustable colour scales to be applied to the various omics data and performed the automatic extraction and visualization of the most significant changes in the datasets. For illustration purpose, the approach was applied to the central carbon metabolism of Escherichia coli. The obtained network contained 774 components and 1232 interactions, highlighting the complexity of bacterial multi-level regulations. The structured representation of this network represents a valuable resource for systemic studies of E. coli, as illustrated from the application to multi-omics data. Some current issues in network representation are discussed on the basis of this work

Sources of Community Health Worker Motivation: A Qualitative Study in Morogoro Region, Tanzania.

There is a renewed interest in community health workers (CHWs) in Tanzania, but also a concern that low motivation of CHWs may decrease the benefits of investments in CHW programs. This study aimed to explore sources of CHW motivation to inform programs in Tanzania and similar contexts. We conducted semi-structured interviews with 20 CHWs in Morogoro Region, Tanzania. Interviews were digitally recorded, transcribed, and coded prior to translation and thematic analysis. The authors then conducted a literature review on CHW motivation and a framework that aligned with our findings was modified to guide the presentation of results. Sources of CHW motivation were identified at the individual, family, community, and organizational levels. At the individual level, CHWs are predisposed to volunteer work and apply knowledge gained to their own problems and those of their families and communities. Families and communities supplement other sources of motivation by providing moral, financial, and material support, including service fees, supplies, money for transportation, and help with farm work and CHW tasks. Resistance to CHW work exhibited by families and community members is limited. The organizational level (the government and its development partners) provides motivation in the form of stipends, potential employment, materials, training, and supervision, but inadequate remuneration and supplies discourage CHWs. Supervision can also be dis-incentivizing if perceived as a sign of poor performance. Tanzanian CHWs who work despite not receiving a salary have an intrinsic desire to volunteer, and their motivation often derives from support received from their families when other sources of motivation are insufficient. Policy-makers and program managers should consider the burden that a lack of remuneration imposes on the families of CHWs. In addition, CHWs' intrinsic desire to volunteer does not preclude a desire for external rewards. Rather, adequate and formal financial incentives and in-kind alternatives would allow already-motivated CHWs to increase their commitment to their work

Altered Neural and Behavioral Dynamics in Huntington's Disease: An Entropy Conservation Approach

Background: Huntington’s disease (HD) is an inherited condition that results in neurodegeneration of the striatum, the forebrain structure that processes cortical information for behavioral output. In the R6/2 transgenic mouse model of HD, striatal neurons exhibit aberrant firing patterns that are coupled with reduced flexibility in the motor system. The aim of this study was to test the patterns of unpredictability in brain and behavior in wild-type (WT) and R6/2 mice. Methodology/Principal Findings: Striatal local field potentials (LFP) were recorded from 18 WT and 17 R6/2 mice (aged 8– 11 weeks) while the mice were exploring a plus-shaped maze. We targeted LFP activity for up to 2 s before and 2 s after each choice-point entry. Approximate Entropy (ApEn) was calculated for LFPs and Shannon Entropy was used to measure the probability of arm choice, as well as the likelihood of making consecutive 90-degree turns in the maze. We found that although the total number of choice-point crossings and entropy of arm-choice probability was similar in both groups, R6/2 mice had more predictable behavioral responses (i.e., were less likely to make 90-degree turns and perform them in alternation with running straight down the same arm), while exhibiting more unpredictable striatal activity, as indicated by higher ApEn values. In both WT and R6/2 mice, however, behavioral unpredictability was negatively correlated with LFP ApEn. Conclusions/Significance: HD results in a perseverative exploration of the environment, occurring in concert with mor

An elaborated feeding cycle model for reductions in vectorial capacity of night-biting mosquitoes by insecticide-treated nets

BACKGROUND: Insecticide Treated Nets (ITNs) are an important tool for malaria control. ITNs are effective because they work on several parts of the mosquito feeding cycle, including both adult killing and repelling effects. METHODS: Using an elaborated description of the classic feeding cycle model, simple formulas have been derived to describe how ITNs change mosquito behaviour and the intensity of malaria transmission, as summarized by vectorial capacity and EIR. The predicted changes are illustrated as a function of the frequency of ITN use for four different vector populations using parameter estimates from the literature. RESULTS: The model demonstrates that ITNs simultaneously reduce mosquitoes' lifespans, lengthen the feeding cycle, and by discouraging human biting divert more bites onto non-human hosts. ITNs can substantially reduce vectorial capacity through small changes to all of these quantities. The total reductions in vectorial capacity differ, moreover, depending on baseline behavior in the absence of ITNs. Reductions in lifespan and vectorial capacity are strongest for vector species with high baseline survival. Anthropophilic and zoophilic species are affected differently by ITNs; the feeding cycle is lengthened more for anthrophilic species, and the proportion of bites that are diverted onto non-human hosts is higher for zoophilic species. CONCLUSION: This model suggests that the efficacy of ITNs should be measured as a total reduction in transmission intensity, and that the quantitative effects will differ by species and by transmission intensity. At very high rates of ITN use, ITNs can generate large reductions in transmission intensity that could provide very large reductions in transmission intensity, and effective malaria control in some areas, especially when used in combination with other control measures. At high EIR, ITNs will probably not substantially reduce the parasite rate, but when transmission intensity is low, reductions in vectorial capacity combine with reductions in the parasite rate to generate very large reductions in EIR