An improvement in clear-air turbulence forecasting based on spontaneous imbalance theory: the ULTURB algorithm

Recent research has shown that Lighthill–Ford spontaneous gravity wave generation theory, when applied to numerical model data, can help predict areas of clear-air turbulence. It is hypothesized that this is the case because spontaneously generated atmospheric gravity waves may initiate turbulence by locally modifying the stability and wind shear. As an improvement on the original research, this paper describes the creation of an ‘operational’ algorithm (ULTURB) with three modifications to the original method: (1) extending the altitude range for which the method is effective downward to the top of the boundary layer, (2) adding turbulent kinetic energy production from the environment to the locally produced turbulent kinetic energy production, and, (3) transforming turbulent kinetic energy dissipation to eddy dissipation rate, the turbulence metric becoming the worldwide ‘standard’. In a comparison of ULTURB with the original method and with the Graphical Turbulence Guidance second version (GTG2) automated procedure for forecasting mid- and upper-level aircraft turbulence ULTURB performed better for all turbulence intensities. Since ULTURB, unlike GTG2, is founded on a self-consistent dynamical theory, it may offer forecasters better insight into the causes of the clear-air turbulence and may ultimately enhance its predictability.

Metabolism of anthocyanins by human gut microflora and their influence on gut bacterial growth

Consumption of anthocyanins has been related with beneficial health effects. However, bioavailability studies have shown low concentration of anthocyanins in plasma and urine. In this study, we have investigated the bacterial-dependent metabolism of malvidin-3-glucoside, gallic acid and a mixture of anthocyanins using a pH-controlled, stirred, batch-culture fermentation system reflective of the distal human large intestine conditions. Most anthocyanins have disappeared after 5 h incubation while gallic acid remained constant through the first 5 h and was almost completely degraded following 24 h of fermentation. Incubation of malvidin-3-glucoside with fecal bacteria mainly resulted in the formation of syringic acid, while the mixture of anthocyanins resulted in formation of gallic, syringic and p-coumaric acids. All the anthocyanins tested enhanced significantly the growth of Bif idobacterium spp. and Lactobacillus−Enterococcus spp. These results suggest that anthocyanins and their metabolites may exert a positive modulation of the intestinal bacterial population.

Theoretical insights into bacterial chemotaxis

Research into understanding bacterial chemotactic systems has become a paradigm for Systems Biology. Experimental and theoretical researchers have worked hand-in-hand for over 40 years to understand the intricate behavior driving bacterial species, in particular how such small creatures, usually not more than 5 µm in length, detect and respond to small changes in their extracellular environment. In this review we highlight the importance that theoretical modeling has played in providing new insight and understanding into bacterial chemotaxis. We begin with an overview of the bacterial chemotaxis sensory response, before reviewing the role of theoretical modeling in understanding elements of the system on the single cell scale and features underpinning multiscale extensions to population models. WIREs Syst Biol Med 2012 doi: 10.1002/wsbm.1168 For further resources related to this article, please visit the WIREs website.

An elastic net orthogonal forward regression algorithm

In this paper we propose an efficient two-level model identification method for a large class of linear-in-the-parameters models from the observational data. A new elastic net orthogonal forward regression (ENOFR) algorithm is employed at the lower level to carry out simultaneous model selection and elastic net parameter estimation. The two regularization parameters in the elastic net are optimized using a particle swarm optimization (PSO) algorithm at the upper level by minimizing the leave one out (LOO) mean square error (LOOMSE). Illustrative examples are included to demonstrate the effectiveness of the new approaches.

A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

A modified rapid enzymatic microtiter plate assay for the quantification of intracellular γ-aminobutyric acid and succinate semialdehyde in bacterial cells

The GABase assay is widely used to rapidly and accurately quantify levels of extracellular γ-aminobutyric acid (GABA). Here we demonstrate a modification of this assay that enables quantification of intracellular GABA in bacterial cells. Cells are lysed by boiling and ethanolamine-O-sulphate, a GABA transaminase inhibitor is used to distinguish between GABA and succinate semialdehyde.

Role of glutamate metabolism in bacterial responses towards acid and other stresses

Glutamate plays a central role in a wide range of metabolic processes in bacterial cells. This review focuses on the involvement of glutamate in bacterial stress responses. In particular it reviews the role of glutamate metabolism in response against acid stress and other stresses. The glutamate decarboxylase (GAD) system has been implicated in acid tolerance in several bacterial genera. This system facilitates intracellular pH homeostasis by consuming protons in a decarboxylation reaction that produces γ-aminobutyrate (GABA) from glutamate. An antiporter system is usually present to couple the uptake of glutamate to the efflux of GABA. Recent insights into the functioning of this system will be discussed. Finally the intracellular fate of GABA will also be discussed. Many bacteria are capable of metabolising GABA to succinate via the GABA shunt pathway. The role and regulation of this pathway will be addressed in the review. © 2012 The Authors Journal of Applied Microbiology © 2012 The Society for Applied Microbiology.

Nanoscale zerovalent iron alters soil bacterial community structure and inhibits chloroaromatic biodegradation potential in Aroclor 1242-contaminated soil

Nanoscale zerovalent iron (nZVI) has potential for the remediation of organochlorine-contaminated environments. Environmental safety concerns associated with in situ deployment of nZVI include potential negative impacts on indigenous microbes whose biodegradative functions could contribute to contaminant remediation. With respect to a two-step polychlorinated biphenyl remediation scenario comprising nZVI dechlorination followed by aerobic biodegradation, we examined the effect of polyacrylic acid (PAA)-coated nZVI (mean diameter = 12.5 nm) applied at 10 g nZVI kg−1 to Aroclor-1242 contaminated and uncontaminated soil over 28 days. nZVI had a limited effect on Aroclor congener profiles, but, either directly or indirectly via changes to soil physico-chemical conditions (pH, Eh), nZVI addition caused perturbation to soil bacterial community composition, and reduced the activity of chloroaromatic mineralizing microorganisms. We conclude that nZVI addition has the potential to inhibit microbial functions that could be important for PCB remediation strategies combining nZVI treatment and biodegradation.

Spirochaetes and other bacterial species associated with bovine digital dermatitis

The 16S rRNA genes from spirochaetes associated with digital dermatitis of British cattle were amplified by polymerase chain reaction from digital dermatitis lesion biopsies using one universal and one treponeme-specific primer. Two treponemal sequences were identified both of which shared a high degree of homology with the oral pathogen Treponema denticola (98%). Two further 16S rRNA gene sequences were obtained and shared similarity to Bacteroides levii (99%) and Mycoplasma hyopharyngis (98%). Polymerase chain reaction with T. denticola-specific primers amplified a potential virulence gene from digital dermatitis lesions which shared a high degree of homology to the 46-kDa haemolysin gene of T. denticola. The significance of the presence of organisms in digital dermatitis lesions of the bovine foot which are closely related to oral pathogens is discussed.

In vivo characterization of Lactobacillus johnsonii FI9785 for use as a defined competitive exclusion agent against bacterial pathogens in poultry

Aims: To test the efficacy of Lactobacillus johnsonii FI9785 in reducing the colonization and shedding of Salmonella enterica serotype Enteritidis, Escherichia coli O78:K80 and Clostridium perfringens in poultry. Methods and Results: Specific pathogen-free chicks (1 day old) were dosed with a single oral inoculum of 1 x 10(9) CFU. Lactobacillus johnsonii FI9785 and 24 h later were challenged in separate experiments with S. Enteritidis (S1400, nal(r)) and E. coli O78:K80 (EC34195, nal(r)). There were no significant effects against S. Enteritidis whereas colonization of the small intestine by E. coli O78:K80 was reduced significantly. Both S. Enteritidis and E. coli colonized the caeca and colon to levels equivalent to control birds and there was no reduction in shedding as assessed by a semi-quantitative cloacal swabbing technique. Specific pathogen-free chicks (20 day old) were dosed with a single oral inoculum of 1 x 10(9) CFU L. johnsonii FI9785 and 24 h later were challenged with C. perfringens. A single oral dose of L. johnsonii FI9785 was sufficient to suppress all aspects of colonization and persistence of C. perfringens. Conclusions: Lactobacillus johnsonii FI9785 may be given to poultry for use as a competitive exclusion agent to control C. perfringens. Significance and Impact of the Study: Lactobacillus johnsonii FI9785 may be a valuable tool to control the endemic disease of necrotic enteritis, thereby reducing economic losses associated with reduced use of antimicrobials in the poultry industry.

eRules: a modular adaptive classification rule learning algorithm for data streams

Advances in hardware and software in the past decade allow to capture, record and process fast data streams at a large scale. The research area of data stream mining has emerged as a consequence from these advances in order to cope with the real time analysis of potentially large and changing data streams. Examples of data streams include Google searches, credit card transactions, telemetric data and data of continuous chemical production processes. In some cases the data can be processed in batches by traditional data mining approaches. However, in some applications it is required to analyse the data in real time as soon as it is being captured. Such cases are for example if the data stream is infinite, fast changing, or simply too large in size to be stored. One of the most important data mining techniques on data streams is classification. This involves training the classifier on the data stream in real time and adapting it to concept drifts. Most data stream classifiers are based on decision trees. However, it is well known in the data mining community that there is no single optimal algorithm. An algorithm may work well on one or several datasets but badly on others. This paper introduces eRules, a new rule based adaptive classifier for data streams, based on an evolving set of Rules. eRules induces a set of rules that is constantly evaluated and adapted to changes in the data stream by adding new and removing old rules. It is different from the more popular decision tree based classifiers as it tends to leave data instances rather unclassified than forcing a classification that could be wrong. The ongoing development of eRules aims to improve its accuracy further through dynamic parameter setting which will also address the problem of changing feature domain values.

Digital predistorter design using B-Spline neural network and inverse of De Boor algorithm

This contribution introduces a new digital predistorter to compensate serious distortions caused by memory high power amplifiers (HPAs) which exhibit output saturation characteristics. The proposed design is based on direct learning using a data-driven B-spline Wiener system modeling approach. The nonlinear HPA with memory is first identified based on the B-spline neural network model using the Gauss-Newton algorithm, which incorporates the efficient De Boor algorithm with both B-spline curve and first derivative recursions. The estimated Wiener HPA model is then used to design the Hammerstein predistorter. In particular, the inverse of the amplitude distortion of the HPA's static nonlinearity can be calculated effectively using the Newton-Raphson formula based on the inverse of De Boor algorithm. A major advantage of this approach is that both the Wiener HPA identification and the Hammerstein predistorter inverse can be achieved very efficiently and accurately. Simulation results obtained are presented to demonstrate the effectiveness of this novel digital predistorter design.

Croig Cave: a late Bronze Age ornament deposition and 3,500 years of coastal foraging in NW Mull, Scotland

Activity within caves provides an important element of the later prehistoric and historic settlement pattern of western Scotland. This contribution reports on a small-scale excavation within Croig Cave, on the coast of north-west Mull, that exposed a 1.95m sequence of midden deposits and cave floors that dated bewteen c 1700 BC and AD 1400. Midden analysis indicated the processing of a .... 950 BC, a penannular copper bracelet a discrete ritual episode within the cycle of otherwise potentially mundane activities. Lead isotope analysis indicates an Irish origin for the copper ore. A piece of iron slag within later midden deposits, dated to c 400 BC, along with high frequencies of wood charcoal, suggest that smithing or smelting may have occurred within the cave. High zinc levels in the historic levels of the midden c AD 1200 might indicate intensive processing of seaweed.

Femtosecond pulse shaping using differential evolutionary algorithm and wavelet operators

Evolutionary meta-algorithms for pulse shaping of broadband femtosecond duration laser pulses are proposed. The genetic algorithm searching the evolutionary landscape for desired pulse shapes consists of a population of waveforms (genes), each made from two concatenated vectors, specifying phases and magnitudes, respectively, over a range of frequencies. Frequency domain operators such as mutation, two-point crossover average crossover, polynomial phase mutation, creep and three-point smoothing as well as a time-domain crossover are combined to produce fitter offsprings at each iteration step. The algorithm applies roulette wheel selection; elitists and linear fitness scaling to the gene population. A differential evolution (DE) operator that provides a source of directed mutation and new wavelet operators are proposed. Using properly tuned parameters for DE, the meta-algorithm is used to solve a waveform matching problem. Tuning allows either a greedy directed search near the best known solution or a robust search across the entire parameter space.