A distributed architecture for the monitoring and analysis of time series data

It is estimated that the quantity of digital data being transferred, processed or stored at any one time currently stands at 4.4 zettabytes (4.4 × 2 70 bytes) and this figure is expected to have grown by a factor of 10 to 44 zettabytes by 2020. Exploiting this data is, and will remain, a significant challenge. At present there is the capacity to store 33% of digital data in existence at any one time; by 2020 this capacity is expected to fall to 15%. These statistics suggest that, in the era of Big Data, the identification of important, exploitable data will need to be done in a timely manner. Systems for the monitoring and analysis of data, e.g. stock markets, smart grids and sensor networks, can be made up of massive numbers of individual components. These components can be geographically distributed yet may interact with one another via continuous data streams, which in turn may affect the state of the sender or receiver. This introduces a dynamic causality, which further complicates the overall system by introducing a temporal constraint that is difficult to accommodate. Practical approaches to realising the system described above have led to a multiplicity of analysis techniques, each of which concentrates on specific characteristics of the system being analysed and treats these characteristics as the dominant component affecting the results being sought. The multiplicity of analysis techniques introduces another layer of heterogeneity, that is heterogeneity of approach, partitioning the field to the extent that results from one domain are difficult to exploit in another. The question is asked can a generic solution for the monitoring and analysis of data that: accommodates temporal constraints; bridges the gap between expert knowledge and raw data; and enables data to be effectively interpreted and exploited in a transparent manner, be identified? The approach proposed in this dissertation acquires, analyses and processes data in a manner that is free of the constraints of any particular analysis technique, while at the same time facilitating these techniques where appropriate. Constraints are applied by defining a workflow based on the production, interpretation and consumption of data. This supports the application of different analysis techniques on the same raw data without the danger of incorporating hidden bias that may exist. To illustrate and to realise this approach a software platform has been created that allows for the transparent analysis of data, combining analysis techniques with a maintainable record of provenance so that independent third party analysis can be applied to verify any derived conclusions. In order to demonstrate these concepts, a complex real world example involving the near real-time capturing and analysis of neurophysiological data from a neonatal intensive care unit (NICU) was chosen. A system was engineered to gather raw data, analyse that data using different analysis techniques, uncover information, incorporate that information into the system and curate the evolution of the discovered knowledge. The application domain was chosen for three reasons: firstly because it is complex and no comprehensive solution exists; secondly, it requires tight interaction with domain experts, thus requiring the handling of subjective knowledge and inference; and thirdly, given the dearth of neurophysiologists, there is a real world need to provide a solution for this domain

Evaluation of HER2, p53, bcl-2, topoisomerase II-alpha, heat shock proteins 27 and 70 in primary breast cancer and metastatic ipsilateral axillary lymph nodes.

BACKGROUND: Breast cancer is a heterogeneous disease. Predictive biological markers (BM) of responsiveness to therapy need to be identified. Evaluation of BM is mainly done at the primary site. However, in the adjuvant therapy of breast cancer, the main goal is control of micrometastases. It is still unknown whether heterogeneity in the expression of BM between the primary site and its micrometastases exists. OBJECTIVE: To evaluate the expression of some BM with potential predictive value from the primary breast cancer site and metastatic ipsilateral axillary lymph nodes. PATIENTS AND METHODS: Focality (percentage of positive cells) and intensity staining scores were evaluated for each marker. Freshly cut sections (4 microm) from embedded blocks of breast cancer fixed in formalin or bouin were put onto superfrost slides (Menzel-Gläser). Protein expression was evaluated immunohistochemically (IHC) using monoclonal antibodies against: topo II-alpha (clone KiS1, 1 microg/ml, Roche) with a trypsine pre-treatment (P); HSP27 (clone G3.1, 1/60, Biogenex), HSP70 (clone BRM.22, 1/80, Biogenex) and HER2 (clone CB11, 1/40, Novocastra; without P); p53 (clone D07, 1/750, Dako) and bcl-2 (clone 124, 1/60, Dako) with citrate buffer as P. RESULTS: Overall, the percentage of discordant marker status in the primary tumour and its metastatic lymph nodes was 2% for HER2, 6% for p53, 15% for bcl-2, 19% for topoisomerase II-alpha, 24% for HSP27 and 30% for HSP70. For the subgroup of patients with positive BM in the primary tumour, the percentage of discordance was 6% for HER2, 7% for p53, 14% for bcl-2, 19% for HSP70, 21% for topoisomerase II-alpha and 36% for HSP27. For the subgroup of patients with positive BM in the lymph nodes, the percentage of discordance was 9% for bcl-2, 15% for HER2 and p53, 21% for topoisomerase II-alpha, 22% for HSP27 and 25% for HSP70. CONCLUSIONS: 1) No biological marker had 100% concordant results. 2) Although some discordant cases might be explained by the limitations of the IHC technique, future studies aiming to evaluate the predictive value of BM in the adjuvant therapy of breast cancer should take into account a possible difference in BM expression between the primary and the metastatic sites.

Plate-specific gain map correction for the improvement of detective quantum efficiency in computed radiography.

PURPOSE: The purpose of this work is to improve the noise power spectrum (NPS), and thus the detective quantum efficiency (DQE), of computed radiography (CR) images by correcting for spatial gain variations specific to individual imaging plates. CR devices have not traditionally employed gain-map corrections, unlike the case with flat-panel detectors, because of the multiplicity of plates used with each reader. The lack of gain-map correction has limited the DQE(f) at higher exposures with CR. This current work describes a feasible solution to generating plate-specific gain maps. METHODS: Ten high-exposure open field images were taken with an RQA5 spectrum, using a sixth generation CR plate suspended in air without a cassette. Image values were converted to exposure, the plates registered using fiducial dots on the plate, the ten images averaged, and then high-pass filtered to remove low frequency contributions from field inhomogeneity. A gain-map was then produced by converting all pixel values in the average into fractions with mean of one. The resultant gain-map of the plate was used to normalize subsequent single images to correct for spatial gain fluctuation. To validate performance, the normalized NPS (NNPS) for all images was calculated both with and without the gain-map correction. Variations in the quality of correction due to exposure levels, beam voltage/spectrum, CR reader used, and registration were investigated. RESULTS: The NNPS with plate-specific gain-map correction showed improvement over the noncorrected case over the range of frequencies from 0.15 to 2.5 mm(-1). At high exposure (40 mR), NNPS was 50%-90% better with gain-map correction than without. A small further improvement in NNPS was seen from carefully registering the gain-map with subsequent images using small fiducial dots, because of slight misregistration during scanning. Further improvement was seen in the NNPS from scaling the gain map about the mean to account for different beam spectra. CONCLUSIONS: This study demonstrates that a simple gain-map can be used to correct for the fixed-pattern noise in a given plate and thus improve the DQE of CR imaging. Such a method could easily be implemented by manufacturers because each plate has a unique bar code and the gain-map for all plates associated with a reader could be stored for future retrieval. These experiments indicated that an improvement in NPS (and hence, DQE) is possible, depending on exposure level, over a wide range of frequencies with this technique.

A mathematical theory of stochastic microlensing. II. Random images, shear, and the Kac-Rice formula

Continuing our development of a mathematical theory of stochastic microlensing, we study the random shear and expected number of random lensed images of different types. In particular, we characterize the first three leading terms in the asymptotic expression of the joint probability density function (pdf) of the random shear tensor due to point masses in the limit of an infinite number of stars. Up to this order, the pdf depends on the magnitude of the shear tensor, the optical depth, and the mean number of stars through a combination of radial position and the star's mass. As a consequence, the pdf's of the shear components are seen to converge, in the limit of an infinite number of stars, to shifted Cauchy distributions, which shows that the shear components have heavy tails in that limit. The asymptotic pdf of the shear magnitude in the limit of an infinite number of stars is also presented. All the results on the random microlensing shear are given for a general point in the lens plane. Extending to the general random distributions (not necessarily uniform) of the lenses, we employ the Kac-Rice formula and Morse theory to deduce general formulas for the expected total number of images and the expected number of saddle images. We further generalize these results by considering random sources defined on a countable compact covering of the light source plane. This is done to introduce the notion of global expected number of positive parity images due to a general lensing map. Applying the result to microlensing, we calculate the asymptotic global expected number of minimum images in the limit of an infinite number of stars, where the stars are uniformly distributed. This global expectation is bounded, while the global expected number of images and the global expected number of saddle images diverge as the order of the number of stars. © 2009 American Institute of Physics.

Magnetic resonance water proton relaxation in protein solutions and tissue: T(1rho) dispersion characterization.

BACKGROUND: Image contrast in clinical MRI is often determined by differences in tissue water proton relaxation behavior. However, many aspects of water proton relaxation in complex biological media, such as protein solutions and tissue are not well understood, perhaps due to the limited empirical data. PRINCIPAL FINDINGS: Water proton T(1), T(2), and T(1rho) of protein solutions and tissue were measured systematically under multiple conditions. Crosslinking or aggregation of protein decreased T(2) and T(1rho), but did not change high-field T(1). T(1rho) dispersion profiles were similar for crosslinked protein solutions, myocardial tissue, and cartilage, and exhibited power law behavior with T(1rho)(0) values that closely approximated T(2). The T(1rho) dispersion of mobile protein solutions was flat above 5 kHz, but showed a steep curve below 5 kHz that was sensitive to changes in pH. The T(1rho) dispersion of crosslinked BSA and cartilage in DMSO solvent closely resembled that of water solvent above 5 kHz but showed decreased dispersion below 5 kHz. CONCLUSIONS: Proton exchange is a minor pathway for tissue T(1) and T(1rho) relaxation above 5 kHz. Potential models for relaxation are discussed, however the same molecular mechanism appears to be responsible across 5 decades of frequencies from T(1rho) to T(1).

The effect of a urinary incontinence self-management program for older women in South Korea: A pilot study

© 2015 Chinese Nursing Association.Background Although self-management approaches have shown strong evidence of positive outcomes for urinary incontinence prevention and management, few programs have been developed for Korean rural communities. Objectives This pilot study aimed to develop, implement, and evaluate a urinary incontinence self-management program for community-dwelling women aged 55 and older with urinary incontinence in rural South Korea. Methods This study used a one-group pre- post-test design to measure the effects of the intervention using standardized urinary incontinence symptom, knowledge, and attitude measures. Seventeen community-dwelling older women completed weekly 90-min group sessions for 5 weeks. Descriptive statistics and paired t-tests and were used to analyze data. Results The mean of the overall interference on daily life from urine leakage (pre-test: M = 5.76 ± 2.68, post-test: M = 2.29 ± 1.93, t = -4.609, p < 0.001) and the sum of International Consultation on Incontinence Questionnaire scores (pre-test: M = 11.59 ± 3.00, post-test: M = 5.29 ± 3.02, t = -5.881, p < 0.001) indicated significant improvement after the intervention. Improvement was also noted on the mean knowledge (pre-test: M = 19.07 ± 3.34, post-test: M = 23.15 ± 2.60, t = 7.550, p < 0.001) and attitude scores (pre-test: M = 2.64 ± 0.19, post-test: M = 3.08 ± 0.41, t = 5.150, p < 0.001). Weekly assignments were completed 82.4% of the time. Participants showed a high satisfaction level (M = 26.82 ± 1.74, range 22-28) with the group program. Conclusions Implementation of a urinary incontinence self-management program was accompanied by improved outcomes for Korean older women living in rural communities who have scarce resources for urinary incontinence management and treatment. Urinary incontinence self-management education approaches have potential for widespread implementation in nursing practice.

Role of DNA binding sites and slow unbinding kinetics in titration-based oscillators.

Genetic oscillators, such as circadian clocks, are constantly perturbed by molecular noise arising from the small number of molecules involved in gene regulation. One of the strongest sources of stochasticity is the binary noise that arises from the binding of a regulatory protein to a promoter in the chromosomal DNA. In this study, we focus on two minimal oscillators based on activator titration and repressor titration to understand the key parameters that are important for oscillations and for overcoming binary noise. We show that the rate of unbinding from the DNA, despite traditionally being considered a fast parameter, needs to be slow to broaden the space of oscillatory solutions. The addition of multiple, independent DNA binding sites further expands the oscillatory parameter space for the repressor-titration oscillator and lengthens the period of both oscillators. This effect is a combination of increased effective delay of the unbinding kinetics due to multiple binding sites and increased promoter ultrasensitivity that is specific for repression. We then use stochastic simulation to show that multiple binding sites increase the coherence of oscillations by mitigating the binary noise. Slow values of DNA unbinding rate are also effective in alleviating molecular noise due to the increased distance from the bifurcation point. Our work demonstrates how the number of DNA binding sites and slow unbinding kinetics, which are often omitted in biophysical models of gene circuits, can have a significant impact on the temporal and stochastic dynamics of genetic oscillators.

Localization in systems of non-identical oscillators

A singular perturbation method is applied to a non-conservative system of two weakly coupled strongly nonlinear non-identical oscillators. For certain parameters, localized solutions exist for which the amplitude of one oscillator is an order of magnitude smaller than the other. It is shown that these solutions are described by coupled equations for the phase difference and scaled amplitudes. Three types of localized solutions are obtained as solutions to these equations which correspond to phase locking, phase drift, and phase entrainment. Quantitative results for the phases and amplitudes of the oscillators and the stability of these phenomena are expressed in terms of the parameters of the model.

Temporal representation of state transitions

This paper describes a knowledge-based temporal representation of state transitions for industrial real-time systems. To allow expression of uncertainty, we shall define fluents as disjuncts of positive/negative time-varying properties. A state of the world is represented as a collection of fluents, which is usually incomplete in the sense that neither the positive form nor the negative form of some properties can be implied from it. The world under consideration is assumed to persist in a given state until an action(s) takes place to effect a transition of it into another state, where actions may either be instantaneous or durative. High-level causal laws are characterized in terms of relationships between actions and the involved world states. An effect completion axiom is imposed on each causal law to guarantee that all the fluents that can be affected by the performance of the corresponding action are governed. This completion requirement is practical for most industrial real-time applications and in fact provides a simple and effective treatment to the so-called frame problem.

An improved result of exponential stability of stochastic semilinear evolution equations

Sufficient conditions for the exponential stability of a class ofnonlinear, non-autonomous stochastic differential equations in infinitedimensions are studied. The analysis consists of introducing a suitableapproximating solution systems and using a limiting argument to pass onstability of strong solutions to mild ones. As a consequence, the classicalcriteriaof stability in A. Ichikawa [8] are improved and extended to cover a class ofnon-autonomous stochastic evolution equations.Two examples are investigated to illustrate our theory.

Finite volume methods applied to the computational modelling of welding phenomena

This paper presents the computational modelling of welding phenomena within a versatile numerical framework. The framework embraces models from both the fields of computational fluid dynamics (CFD) and computational solid mechanics (CSM). With regard to the CFD modelling of the weld pool fluid dynamics, heat transfer and phase change, cell-centred finite volume (FV) methods are employed. Additionally, novel vertex-based FV methods are employed with regard to the elasto-plastic deformation associated with the CSM. The FV methods are included within an integrated modelling framework, PHYSICA, which can be readily applied to unstructured meshes. The modelling techniques are validated against a variety of reference solutions.

Aqueous solution of anionic surfactants mixed with soils show a synergistic reduction in surface tension

Water retention and transport in soils is dependent upon the surface tension of the aqueous phase. Surfactants present in aqueous solution reduce the surface tension of aqueous phase. In soil–water systems, this can result in water drainage and reductions in field capacity and hydraulic conductivity. In this investigation, the surface tension of surfactant solutions mixed with soil—in a constant fixed ratio—was measured as a function of surfactant concentration. Two anionic surfactants were used: sodium dodecyl sulphate and sodium bis (2-ethylhexyl) sulfosuccinate. Two soils were also used—a clay soil and a sandy soil. The key observation made by this investigation was that the addition of soil to the surfactant solution provided a further component of surface tension reduction. Neither soil sample reduced the surface tension of water when surfactant was absent from the aqueous phase, though both soils released soil organic matter at low surfactant concentrations as shown by measurement of the chemical oxygen demand of the supernatant solutions. Furthermore, both surfactants were shown to be weakly adsorbed by soil as shown by the use of a methylene blue assay. It is therefore proposed that the additional reduction in surface tension arises from synergistic interactions between the surfactants and dissolved soil organic matter.

Investigation of the permeation of model formulations and a commercial ibuprofen formulation in Carbosil® and human skin using ATR-FTIR and multivariate spectral analysis

The purpose of the present study was to use attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and target factor analysis (TFA) to investigate the permeation of model drugs and formulation components through Carbosil® membrane and human skin. Diffusion studies of saturated solutions in 50:50 water/ethanol of methyl paraben (MP), ibuprofen (IBU) and caffeine (CF) were performed on Carbosil® membrane. The spectroscopic data were analysed by target factor analysis, and evolution profiles of the signal for each component (i.e. the drug, water, ethanol and membrane) over time were obtained. Results showed that the data were successfully deconvoluted as correlations between factors from the data and reference spectra of the components, were above 0.8 in all cases. Good reproducibility over three runs for the evolution profiles was obtained. From the evolution profiles it was observed that water diffused better through the Carbosil® membrane than ethanol, confirming the hydrophilic properties of the Carbosil® membrane used. IBU diffused slower compared with MP and CF. The evolution profile of CF was very similar to that of water, probably because of the high solubility of CF in water, indicating that both compounds are diffusing concurrently. The second part of the work involved a study of the evolution profiles of the components of a commercial topical gel containing 5% (w/w) of ibuprofen as it permeated through human skin. Although the system was much more complex, data were still successfully deconvoluted and the different components of the formulation identified except for benzyl alcohol which might be attributed to the low concentrations of benzyl alcohol used in topical formulations. (C) 2009 Elsevier B.V. All rights reserved.

Influence of the Pacific Decadal Oscillation on phytoplankton phenology and community structure in the western North Pacific

Phytoplankton phenology and community structure in the western North Pacific were investigated for 2001–2009, based on satellite ocean colour data and the Continuous Plankton Recorder survey. We estimated the timing of the spring bloom based on the cumulative sum satellite chlorophyll adata, and found that the Pacific Decadal Oscillation (PDO)-related interannual SST anomaly in spring significantly affected phytoplankton phenology. The bloom occurred either later or earlier in years of positive or negative PDO (indicating cold and warm conditions, respectively). Phytoplankton composition in the early summer varied depending on the magnitude of seasonal SST increases, rather than the SST value itself. Interannual variations in diatom abundance and the relative abundance of non-diatoms were positively correlated with SST increases for March–April and May–July, respectively, suggesting that mixed layer environmental factors, such as light availability and nutrient stoichiometry, determine shifts in phytoplankton community structure. Our study emphasised the importance of the interannual variation in climate-induced warm–cool cycles as one of the key mechanisms linking climatic forcing and lower trophic level ecosystems.

Potential impacts of climate change on the primary production of regional seas: A comparative analysis of five European seas

Regional seas are potentially highly vulnerable to climate change, yet are the most directly societally important regions of the marine environment. The combination of widely varying conditions of mixing, forcing, geography (coastline and bathymetry) and exposure to the open-ocean makes these seas subject to a wide range of physical processes that mediates how large scale climate change impacts on these seas’ ecosystems. In this paper we explore the response of five regional sea areas to potential future climate change, acting via atmospheric, oceanic and terrestrial vectors. These include the Barents Sea, Black Sea, Baltic Sea, North Sea, Celtic Seas, and are contrasted with a region of the Northeast Atlantic. Our aim is to elucidate the controlling dynamical processes and how these vary between and within these seas. We focus on primary production and consider the potential climatic impacts on: long term changes in elemental budgets, seasonal and mesoscale processes that control phytoplankton’s exposure to light and nutrients, and briefly direct temperature response. We draw examples from the MEECE FP7 project and five regional model systems each using a common global Earth System Model as forcing. We consider a common analysis approach, and additional sensitivity experiments. Comparing projections for the end of the 21st century with mean present day conditions, these simulations generally show an increase in seasonal and permanent stratification (where present). However, the first order (low- and mid-latitude) effect in the open ocean projections of increased permanent stratification leading to reduced nutrient levels, and so to reduced primary production, is largely absent, except in the NE Atlantic. Even in the two highly stratified, deep water seas we consider (Black and Baltic Seas) the increase in stratification is not seen as a first order control on primary production. Instead, results show a highly heterogeneous picture of positive and negative change arising from complex combinations of multiple physical drivers, including changes in mixing, circulation and temperature, which act both locally and non-locally through advection.