Tuning of Human Modulation Filters Is Carrier-Frequency Dependent

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Toward optimal implementation of cancer prevention and control programs in public health: A study protocol on mis-implementation

Abstract Background Much of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes. Methods This is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation. Discussion This study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas

Light regime characterization in an airlift photobioreactor for production of microalgae with high starch content

The slow development of microalgal biotechnology is due to the failure in the design of large-scale photobioreactors (PBRs) where light energy is efficiently utilized. In this work, both the quality and the amount of light reaching a given point of the PBR were determined and correlated with cell density, light path length, and PBR geometry. This was made for two different geometries of the downcomer of an airlift PBR using optical fiber technology that allows to obtain information about quantitative and qualitative aspects of light patterns. This is important since the ability of microalgae to use the energy of photons is different, depending on the wavelength of the radiation. The results show that the circular geometry allows a more efficient light penetration, especially in the locations with a higher radial coordinate (r) when compared to the plane geometry; these observations were confirmed by the occurrence of a higher fraction of illuminated volume of the PBR for this geometry. An equation is proposed to correlate the relative light intensity with the penetration distance for both geometries and different microalgae cell concentrations. It was shown that the attenuation of light intensity is dependent on its wavelength, cell concentration, geometry of PBR, and the penetration distance of light.Fundação para a Ciência e a Tecnologia (FCT

The utilisation of health research in policy-making: Concepts, examples and methods of assessment

The importance of health research utilisation in policy-making, and of understanding the mechanisms involved, is increasingly recognised. Recent reports calling for more resources to improve health in developing countries, and global pressures for accountability, draw greater attention to research-informed policy-making. Key utilisation issues have been described for at least twenty years, but the growing focus on health research systems creates additional dimensions. The utilisation of health research in policy-making should contribute to policies that may eventually lead to desired outcomes, including health gains. In this article, exploration of these issues is combined with a review of various forms of policy-making. When this is linked to analysis of different types of health research, it assists in building a comprehensive account of the diverse meanings of research utilisation. Previous studies report methods and conceptual frameworks that have been applied, if with varying degrees of success, to record utilisation in policy-making. These studies reveal various examples of research impact within a general picture of underutilisation. Factors potentially enhancing utilisation can be identified by exploration of: priority setting; activities of the health research system at the interface between research and policy-making; and the role of the recipients, or 'receptors', of health research. An interfaces and receptors model provides a framework for analysis. Recommendations about possible methods for assessing health research utilisation follow identification of the purposes of such assessments. Our conclusion is that research utilisation can be better understood, and enhanced, by developing assessment methods informed by conceptual analysis and review of previous studies

Phenotypic Variation and Bistable Switching in Bacteria

Microbial research generally focuses on clonal populations. However, bacterial cells with identical genotypes frequently display different phenotypes under identical conditions. This microbial cell individuality is receiving increasing attention in the literature because of its impact on cellular differentiation, survival under selective conditions, and the interaction of pathogens with their hosts. It is becoming clear that stochasticity in gene expression in conjunction with the architecture of the gene network that underlies the cellular processes can generate phenotypic variation. An important regulatory mechanism is the so-called positive feedback, in which a system reinforces its own response, for instance by stimulating the production of an activator. Bistability is an interesting and relevant phenomenon, in which two distinct subpopulations of cells showing discrete levels of gene expression coexist in a single culture. In this chapter, we address techniques and approaches used to establish phenotypic variation, and relate three well-characterized examples of bistability to the molecular mechanisms that govern these processes, with a focus on positive feedback.

A unique genetic code change in the mitochondrial genome of the parasitic nematode Radopholus similis

<p>Abstract</p> <p>Background</p> <p>Mitochondria (mt) contain their own autonomously replicating DNA, constituted as a small circular genome encoding essential subunits of the respiratory chain. Mt DNA is characterized by a genetic code which differs from the standard one. Interestingly, the mt genome of nematodes share some peculiar features, such as small transfer RNAs, truncated ribosomal RNAs and - in the class of Chromadorean nematodes - unidirectional transcription.</p> <p>Findings</p> <p>We present the complete mt genomic sequence (16,791 bp) of the plant-parasitic nematode <it>Radopholus similis </it>(class Chromadorea). Although it has a gene content similar to most other nematodes, many idiosyncrasies characterize the extremely AT-rich mt genome of <it>R. similis </it>(85.4% AT). The secondary structure of the large (16S) rRNA is further reduced, the gene order is unique, the large non-coding region contains two large repeats, and most interestingly, the UAA codon is reassigned from translation termination to tyrosine. In addition, 7 out of 12 protein-coding genes lack a canonical stop codon and analysis of transcriptional data showed the absence of polyadenylation. Northern blot analysis confirmed that only one strand is transcribed and processed. Furthermore, using nucleotide content bias methods, regions for the origin of replication are suggested.</p> <p>Conclusion</p> <p>The extraordinary mt genome of <it>R. similis </it>with its unique genetic code appears to contain exceptional features correlated to DNA decoding. Therefore the genome may provide an incentive to further elucidate these barely understood processes in nematodes. This comprehension may eventually lead to parasitic nematode-specific control targets as healthy mitochondria are imperative for organism survival. In addition, the presented genome is an interesting exceptional event in genetic code evolution.</p

Financial time series prediction using spiking neural networks

In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments. © 2014 Reid et al

The Emergence of Consensus: a primer

The origin of population-scale coordination has puzzled philosophers and scientists for centuries. Recently, game theory, evolutionary approaches and complex systems science have provided quantitative insights on the mechanisms of social consensus. This paper overviews the main dimensions over which the debate has unfolded and discusses some representative results, with a focus on those situations in which consensus emerges `spontaneously' in absence of centralised institutions. Covered topics include the macroscopic consequences of the different microscopic rules of behavioural contagion, the role of social networks, and the mechanisms that prevent the formation of a consensus or alter it after it has emerged. Special attention is devoted to the recent wave of experiments on the emergence of consensus in social systems

Contrasting impacts of heat stress on violent and nonviolent robbery in Beijing, China

Previous studies investigating the relation between heat stress and crime incidents often focus on violent crimes. In this study, the impacts of heat stress on two types of robbery (violent and nonviolent) in China are compared using crime statistics collected in Beijing and heat stress indices that consider the combined effects of temperature and humidity. The results indicate that the abrupt change in the trend of robbery rates is affected by the 2008 Beijing Olympic Games. The nonviolent robbery rates have a more pronounced seasonality and are better correlated with heat stress at daily scales, especially during the period from 2009 to 2014 when no trend exists. The results also demonstrate that both violent and nonviolent robbery rates significantly increase with heat stress in spring. The nonviolent robbery rates also significantly increase with heat stress in summer. The influence of heat stress on violent robbery rate is more complicated and nonlinear

The <i>Pratylenchus penetrans</i> transcriptome as a source for the development of alternative control strategies:mining for putative genes involved in parasitism and evaluation of <i>in planta</i> RNAi

The root lesion nematode Pratylenchus penetrans is considered one of the most economically important species within the genus. Host range studies have shown that nearly 400 plant species can be parasitized by this species. To obtain insight into the transcriptome of this migratory plant-parasitic nematode, we used Illumina mRNA sequencing analysis of a mixed population, as well as nematode reads detected in infected soybean roots 3 and 7 days after nematode infection. Over 140 million paired end reads were obtained for this species, and de novo assembly resulted in a total of 23,715 transcripts. Homology searches showed significant hit matches to 58% of the total number of transcripts using different protein and EST databases. In general, the transcriptome of P. penetrans follows common features reported for other root lesion nematode species. We also explored the efficacy of RNAi, delivered from the host, as a strategy to control P. penetrans, by targeted knock-down of selected nematode genes. Different comparisons were performed to identify putative nematode genes with a role in parasitism, resulting in the identification of transcripts with similarities to other nematode parasitism genes. Focusing on the predicted nematode secreted proteins found in this transcriptome, we observed specific members to be up-regulated at the early time points of infection. In the present study, we observed an enrichment of predicted secreted proteins along the early time points of parasitism by this species, with a significant number being pioneer candidate genes. A representative set of genes examined using RT-PCR confirms their expression during the host infection. The expression patterns of the different candidate genes raise the possibility that they might be involved in critical steps of P. penetrans parasitism. This analysis sheds light on the transcriptional changes that accompany plant infection by P. penetrans, and will aid in identifying potential gene targets for selection and use to design effective control strategies against root lesion nematodes