Development of a generic activities model of command and control

This paper reports on five different models of command and control. Four different models are reviewed: a process model, a contextual control model, a decision ladder model and a functional model. Further to this, command and control activities are analysed in three distinct domains: armed forces, emergency services and civilian services. From this analysis, taxonomies of command and control activities are developed that give rise to an activities model of command and control. This model will be used to guide further research into technological support of command and control activities

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics

The Neural Basis of Object-Context Relationships on Aesthetic Judgment

The relationship between contextual information and object perception has received considerable attention in neuroimaging studies. In the work reported here, we used functional magnetic resonance imaging (fMRI) to investigate the relationship between aesthetic judgment and images of objects in their normal contextual setting versus images of objects in abnormal contextual settings and the underlying brain activity. When object-context relationships are violated changes in visual perception and aesthetic judgment emerges that exposes the contribution of vision to interpretations shaped by previous experience. We found that effects of context on aesthetic judgment modulates different memory sub-systems, while aesthetic judgment regardless of context recruit medial and lateral aspects of the orbitofrontal cortex, consistent with previous findings. Visual cortical areas traditionally associated with the processing of visual features are recruited in normal contexts, irrespective of aesthetic ratings, while prefrontal areas are significantly more engaged when objects are viewed in unaccustomed settings

Model based analysis of real-time PCR data from DNA binding dye protocols

BACKGROUND: Reverse transcription followed by real-time PCR is widely used for quantification of specific mRNA, and with the use of double-stranded DNA binding dyes it is becoming a standard for microarray data validation. Despite the kinetic information generated by real-time PCR, most popular analysis methods assume constant amplification efficiency among samples, introducing strong biases when amplification efficiencies are not the same. RESULTS: We present here a new mathematical model based on the classic exponential description of the PCR, but modeling amplification efficiency as a sigmoidal function of the product yield. The model was validated with experimental results and used for the development of a new method for real-time PCR data analysis. This model based method for real-time PCR data analysis showed the best accuracy and precision compared with previous methods when used for quantification of in-silico generated and experimental real-time PCR results. Moreover, the method is suitable for the analyses of samples with similar or dissimilar amplification efficiency. CONCLUSION: The presented method showed the best accuracy and precision. Moreover, it does not depend on calibration curves, making it ideal for fully automated high-throughput applications

A new real-time PCR method to overcome significant quantitative inaccuracy due to slight amplification inhibition

<p>Abstract</p> <p>Background</p> <p>Real-time PCR analysis is a sensitive DNA quantification technique that has recently gained considerable attention in biotechnology, microbiology and molecular diagnostics. Although, the cycle-threshold (<it>Ct</it>) method is the present "gold standard", it is far from being a standard assay. Uniform reaction efficiency among samples is the most important assumption of this method. Nevertheless, some authors have reported that it may not be correct and a slight PCR efficiency decrease of about 4% could result in an error of up to 400% using the <it>Ct </it>method. This reaction efficiency decrease may be caused by inhibiting agents used during nucleic acid extraction or copurified from the biological sample.</p> <p>We propose a new method (<it>Cy</it>_<it>0</it>) that does not require the assumption of equal reaction efficiency between unknowns and standard curve.</p> <p>Results</p> <p>The <it>Cy</it>_{<it>0 </it>}method is based on the fit of Richards' equation to real-time PCR data by nonlinear regression in order to obtain the best fit estimators of reaction parameters. Subsequently, these parameters were used to calculate the <it>Cy</it>_{<it>0 </it>}value that minimizes the dependence of its value on PCR kinetic.</p> <p>The <it>Ct</it>, second derivative (<it>Cp</it>), sigmoidal curve fitting method (<it>SCF</it>) and <it>Cy</it>_{<it>0 </it>}methods were compared using two criteria: precision and accuracy. Our results demonstrated that, in optimal amplification conditions, these four methods are equally precise and accurate. However, when PCR efficiency was slightly decreased, diluting amplification mix quantity or adding a biological inhibitor such as IgG, the <it>SCF</it>, <it>Ct </it>and <it>Cp </it>methods were markedly impaired while the <it>Cy</it>_{<it>0 </it>}method gave significantly more accurate and precise results.</p> <p>Conclusion</p> <p>Our results demonstrate that <it>Cy</it>_{<it>0 </it>}represents a significant improvement over the standard methods for obtaining a reliable and precise nucleic acid quantification even in sub-optimal amplification conditions overcoming the underestimation caused by the presence of some PCR inhibitors.</p

Lower limb strength training in children with cerebral palsy – a randomized controlled trial protocol for functional strength training based on progressive resistance exercise principles

<p>Abstract</p> <p>Background</p> <p>Until recently, strength training in children with cerebral palsy (CP) was considered to be inappropriate, because it could lead to increased spasticity or abnormal movement patterns. However, the results of recent studies suggest that progressive strength training can lead to increased strength and improved function, but low methodological quality and incomplete reporting on the training protocols hampers adequate interpretation of the results. This paper describes the design and training protocol of a randomized controlled trial to assess the effects of a school-based progressive functional strength training program for children with CP.</p> <p>Methods/Results</p> <p>Fifty-one children with Gross Motor Function Classification Systems levels I to III, aged of 6 to 13 years, were recruited. Using stratified randomization, each child was assigned to an intervention group (strength training) or a control group (usual care). The strength training was given in groups of 4–5 children, 3 times a week, for a period of 12 weeks. Each training session focussed on four exercises out of a 5-exercise circuit. The training load was gradually increased based on the child's maximum level of strength, as determined by the 8 Repetition Maximum (8 RM). To evaluate the effectiveness of the training, all children were evaluated before, during, directly after, and 6 weeks after the intervention period. Primary outcomes in this study were gross motor function (measured with the Gross Motor Function Measure and functional muscle strength tests) and walking ability (measured with the 10-meter, the 1-minute and the timed stair test). Secondary outcomes were lower limb muscle strength (measured with a 6 RM test, isometric strength tests, and a sprint capacity test), mobility (measured with a mobility questionnaire), and sport activities (measured with the Children's Assessment of Participation and Enjoyment). Spasticity and range of motion were assessed to evaluate any adverse events.</p> <p>Conclusion</p> <p>Randomized clinical trials are considered to present the highest level of evidence. Nevertheless, it is of utmost importance to report on the design, the applied evaluation methods, and all elements of the intervention, to ensure adequate interpretation of the results and to facilitate implementation of the intervention in clinical practice if the results are positive.</p> <p>Trial Registration</p> <p>Trial Register NTR1403</p

Heightened resistance to host type 1 interferons characterizes HIV-1 at transmission and after antiretroviral therapy interruption

Type 1 interferons (IFN-I) are potent innate antiviral effectors that constrain HIV-1 transmission. However, harnessing these cytokines for HIV-1 cure strategies has been hampered by an incomplete understanding of their antiviral activities at later stages of infection. Here, we characterized the IFN-I sensitivity of 500 clonally derived HIV-1 isolates from the plasma and CD4+ T cells of 26 individuals sampled longitudinally after transmission or after antiretroviral therapy (ART) and analytical treatment interruption. We determined the concentration of IFNα2 and IFNβ that reduced viral replication in vitro by 50% (IC50) and found consistent changes in the sensitivity of HIV-1 to IFN-I inhibition both across individuals and over time. Resistance of HIV-1 isolates to IFN-I was uniformly high during acute infection, decreased in all individuals in the first year after infection, was reacquired concomitant with CD4+ T cell loss, and remained elevated in individuals with accelerated disease. HIV-1 isolates obtained by viral outgrowth during suppressive ART were relatively IFN-I sensitive, resembling viruses circulating just before ART initiation. However, viruses that rebounded after treatment interruption displayed the highest degree of IFNα2 and IFNβ resistance observed at any time during the infection course. These findings indicate a dynamic interplay between host innate responses and the evolving HIV-1 quasispecies, with the relative contribution of IFN-I to HIV-1 control affected by both ART and analytical treatment interruption. Although elevated at transmission, host innate pressures are the highest during viral rebound, limiting the viruses that successfully become reactivated from latency to those that are IFN-I resistant

Effectiveness of physical therapy interventions for children with cerebral palsy: A systematic review

Background To assess the effectiveness of physical therapy (PT) interventions on functioning in children with cerebral palsy (CP). Methods A search was made in Medline, Cinahl, PEDro and the Cochrane library for the period 1990 to February 2007. Only randomized controlled trials (RCTs) on PT interventions in children with diagnosed CP were included. Two reviewers independently assessed the methodological quality and extracted the data. The outcomes measured in the trials were classified using the International Classification of Functioning, Disability and Health (ICF). Results Twenty-two trials were identified. Eight intervention categories were distinguished. Four trials were of high methodological quality. Moderate evidence of effectiveness was established for two intervention categories: effectiveness of upper extremity treatments on attained goals and active supination, and of prehensile hand treatment and neurodevelopmental therapy (NDT) or NDT twice a week on developmental status, and of constraint-induced therapy on amount and quality of hand use. Moderate evidence of ineffectiveness was found of strength training on walking speed and stride length. Conflicting evidence was found for strength training on gross motor function. For the other intervention categories the evidence was limited due to low methodological quality and the statistically insignificant results of the studies. Conclusion Due to limitations in methodological quality and variations in population, interventions and outcomes, mostly limited evidence on the effectiveness of most PT interventions is available through RCTs. Moderate evidence was found for some effectiveness of upper extremity training. Well-designed trials are needed especially for focused PT interventions.BioMed Central Open acces

A Bayesian Approach to Analyse Genetic Variation within RNA Viral Populations

The development of modern and affordable sequencing technologies has allowed the study of viral populations to an unprecedented depth. This is of particular interest for the study of within-host RNA viral populations, where variation due to error-prone polymerases can lead to immune escape, antiviral resistance and adaptation to new host species. Methods to sequence RNA virus genomes include reverse transcription (RT) and polymerase chain reaction (PCR). RT-PCR is a molecular biology technique widely used to amplify DNA from an RNA template. The method itself relies on the in vitro synthesis of copy DNA from RNA followed by multiple cycles of DNA amplification. However, this method introduces artefactual errors that can act as confounding factors when the sequence data are analysed. Although there are a growing number of published studies exploring the intra- and inter-host evolutionary dynamics of RNA viruses, the complexity of the methods used to generate sequences makes it difficult to produce probabilistic statements about the likely sources of observed sequence variants. This complexity is further compounded as both the depth of sequencing and the length of the genome segment of interest increase. Here we develop a Bayesian method to characterise and differentiate between likely structures for the background viral population. This approach can then be used to identify nucleotide sites that show evidence of change in the within-host viral population structure, either over time or relative to a reference sequence (e.g. an inoculum or another source of infection), or both, without having to build complex evolutionary models. Identification of these sites can help to inform the design of more focussed experiments using molecular biology tools, such as site-directed mutagenesis, to assess the function of specific amino acids. We illustrate the method by applying to datasets from experimental transmission of equine influenza, and a pre-clinical vaccine trial for HIV-1