Widening the gap between measurement and modelling of secondary organic aerosol properties?

The link between measured sub-saturated hygroscopicity and cloud activation potential of secondary organic aerosol particles produced by the chamber photo-oxidation of α-pinene in the presence or absence of ammonium sulphate seed aerosol was investigated using two models of varying complexity. A simple single hygroscopicity parameter model and a more complex model (incorporating surface effects) were used to assess the detail required to predict the cloud condensation nucleus (CCN) activity from the subsaturated water uptake. Sub-saturated water uptake measured by three hygroscopicity tandem differential mobility analyser (HTDMA) instruments was used to determine the water activity for use in the models. The predicted CCN activity was compared to the measured CCN activation potential using a continuous flow CCN counter. Reconciliation using the more complex model formulation with measured cloud activation could be achieved widely different assumed surface tension behavior of the growing droplet; this was entirely determined by the instrument used as the source of water activity data. This unreliable derivation of the water activity as a function of solute concentration from sub-saturated hygroscopicity data indicates a limitation in the use of such data in predicting cloud condensation nucleus behavior of particles with a significant organic fraction. Similarly, the ability of the simpler single parameter model to predict cloud activation behaviour was dependent on the instrument used to measure sub-saturated hygroscopicity and the relative humidity used to provide the model input. However, agreement was observed for inorganic salt solution particles, which were measured by all instruments in agreement with theory. The difference in HTDMA data from validated and extensively used instruments means that it cannot be stated with certainty the detail required to predict the CCN activity from sub-saturated hygroscopicity. In order to narrow the gap between measurements of hygroscopic growth and CCN activity the processes involved must be understood and the instrumentation extensively quality assured. It is impossible to say from the results presented here due to the differences in HTDMA data whether: i) Surface tension suppression occurs ii) Bulk to surface partitioning is important iii) The water activity coefficient changes significantly as a function of the solute concentration.

Nuclear localization of NPR1 is required for activation of PR gene expression

Systemic acquired resistance (SAR) is a broad-spectrum resistance in plants that involves the upregulation of a battery of pathogenesis-related (PR) genes. NPR1 is a key regulator in the signal transduction pathway that leads to SAR. Mutations in NPR1 result in a failure to induce PR genes in systemic tissues and a heightened susceptibility to pathogen infection, whereas overexpression of the NPR1 protein leads to increased induction of the PR genes and enhanced disease resistance. We analyzed the subcellular localization of NPR1 to gain insight into the mechanism by which this protein regulates SAR. An NPR1–green fluorescent protein fusion protein, which functions the same as the endogenous NPR1 protein, was shown to accumulate in the nucleus in response to activators of SAR. To control the nuclear transport of NPR1, we made a fusion of NPR1 with the glucocorticoid receptor hormone binding domain. Using this steroid-inducible system, we clearly demonstrate that nuclear localization of NPR1 is essential for its activity in inducing PR genes.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Striving to realise the European idea : judging the news media’s accounts of how the Berlin Wall gave impetus to a new order across Europe

The 1990 European Community was taken by surprise, by the urgency of demands from the newly-elected Eastern European governments to become member countries. Those governments were honouring the mass social movement of the streets, the year before, demanding free elections and a liberal economic system associated with “Europe”. The mass movement had actually been accompanied by much activity within institutional politics, in Western Europe, the former “satellite” states, the Soviet Union and the United States, to set up new structures – with German reunification and an expanded EC as the centre-piece. This paper draws on the writer’s doctoral dissertation on mass media in the collapse of the Eastern bloc, focused on the Berlin Wall – documenting both public protests and institutional negotiations. For example the writer as a correspondent in Europe from that time, recounts interventions of the German Chancellor, Helmut Kohl, at a European summit in Paris nine days after the “Wall”, and separate negotiations with the French President, Francois Mitterrand -- on the reunification, and EU monetary union after 1992. Through such processes, the “European idea” would receive fresh impetus, though the EU which eventuated, came with many altered expectations. It is argued here that as a result of the shock of 1989, a “social” Europe can be seen emerging, as a shared experience of daily life -- especially among people born during the last two decades of European consolidation. The paper draws on the author’s major research, in four parts: (1) Field observation from the strategic vantage point of a news correspondent. This includes a treatment of evidence at the time, of the wishes and intentions of the mass public (including the unexpected drive to join the European Community), and those of governments, (e.g. thoughts of a “Tienanmen Square solution” in East Berlin, versus the non-intervention policies of the Soviet leader, Mikhail Gorbachev). (2) A review of coverage of the crisis of 1989 by major news media outlets, treated as a history of the process. (3) As a comparison, and a test of accuracy and analysis; a review of conventional histories of the crisis appearing a decade later.(4) A further review, and test, provided by journalists responsible for the coverage of the time, as reflection on practice – obtained from semi-structured interviews.

Delivering value for money in the procurement of public sector major infrastructure : a new first-order decision making model

The significant challenge faced by government in demonstrating value for money in the delivery of major infrastructure resolves around estimating costs and benefits of alternative modes of procurement. Faced with this challenge, one approach is to focus on a dominant performance outcome visible on the opening day of the asset, as the means to select the procurement approach. In this case, value for money becomes a largely nominal concept and determined by selected procurement mode delivering, or not delivering, the selected performance outcome, and notwithstanding possible under delivery on other desirable performance outcomes, as well as possibly incurring excessive transaction costs. This paper proposes a mind-set change in this particular practice, to an approach in which the analysis commences with the conditions pertaining to the project and proceeds to deploy transaction cost and production cost theory to indicate a procurement approach that can claim superior value for money relative to other competing procurement modes. This approach to delivering value for money in relative terms is developed in a first-order procurement decision making model outlined in this paper. The model developed could be complementary to the Public Sector Comparator (PSC) in terms of cross validation and the model more readily lends itself to public dissemination. As a possible alternative to the PSC, the model could save time and money in preparation of project details to lesser extent than that required in the reference project and may send a stronger signal to the market that may encourage more innovation and competition.

Human atrial beta1L-adrenoceptor but not beta3-adrenoceptor activation increases force and Ca2+ current at physiological temperature

BACKGROUND AND PURPOSE It has been proposed that BRL37344, SR58611 and CGP12177 activate b3-adrenoceptors in human atrium to increase contractility and L-type Ca2+ current (ICa-L). b3-adrenoceptor agonists are potentially beneficial for the treatment of a variety of diseases but concomitant cardiostimulation would be potentially harmful. It has also been proposed that (-)-CGP12177 activates the low affinity binding site of the b1-adrenoceptor in human atrium. We therefore used BRL37344, SR58611 and (-)-CGP12177 with selective b-adrenoceptor subtype antagonists to clarify cardiostimulant b-adrenoceptor subtypes in human atrium. EXPERIMENTAL APPROACH Human right atrium was obtained from patients without heart failure undergoing coronary artery bypass or valve surgery. Cardiomyocytes were prepared to test BRL37344, SR58611 and CGP12177 effects on ICa-L. Contractile effects were determined on right atrial trabeculae. KEY RESULTS BRL37344 increased force which was antagonized by blockade of b1- and b2-adrenoceptors but not by blockade of b3-adrenoceptors with b3-adrenoceptor-selective L-748,337 (1 mM). The b3-adrenoceptor agonist SR58611 (1 nM–10 mM) did not affect atrial force. BRL37344 and SR58611 did not increase ICa-L at 37°C, but did at 24°C which was prevented by L-748,337. (-)-CGP12177 increased force and ICa-L at both 24°C and 37°C which was prevented by (-)-bupranolol (1–10 mM), but not L-748,337. CONCLUSIONS AND IMPLICATIONS We conclude that the inotropic responses to BRL37344 are mediated through b1- and b2-adrenoceptors. The inotropic and ICa-L responses to (-)-CGP12177 are mediated through the low affinity site b1L-adrenoceptor of the b1-adrenoceptor. b3-adrenoceptor-mediated increases in ICa-L are restricted to low temperatures. Human atrial b3-adrenoceptors do not change contractility and ICa-L at physiological temperature.

Order and disorder in the structures of two crystal polymorphs of the adduct bis(quinolinium-2-carboxylate) DL-malic acid

The structures of two polymorphs of the anhydrous cocrystal adduct of bis(quinolinium-2-carboxylate) DL-malic acid, one triclinic the other monoclinic and disordered, have been determined at 200 K. Crystals of the triclinic polymorph 1 have space group P-1, with Z = 1 in a cell with dimensions a = 4.4854(4), b = 9.8914(7), c = 12.4670(8)Å, α = 79.671(5), β = 83.094(6), γ = 88.745(6)deg. Crystals of the monoclinic polymorph 2 have space group P21/c, with Z = 2 in a cell with dimensions a = 13.3640(4), b = 4.4237(12), c = 18.4182(5)Å, β = 100.782(3)deg. Both structures comprise centrosymmetric cyclic hydrogen-bonded quinolinic acid zwitterion dimers [graph set R2/2(10)] and 50% disordered malic acid molecules which lie across crystallographic inversion centres. However, the oxygen atoms of the malic acid carboxylic groups in 2 are 50% rotationally disordered whereas in 1 these are ordered. There are similar primary malic acid carboxyl O-H...quinaldic acid hydrogen-bonding chain interactions in each polymorph, extended into two-dimensional structures but in l this involves centrosymmetric cyclic head-to-head malic acid hydroxyl-carboxyl O-H...O interactions [graph set R2/2(10)] whereas in 2 the links are through single hydroxy-carboxyl hydrogen bonds.

Improving the performance of model-order selection criteria by partial-model selection search

The traditional searching method for model-order selection in linear regression is a nested full-parameters-set searching procedure over the desired orders, which we call full-model order selection. On the other hand, a method for model-selection searches for the best sub-model within each order. In this paper, we propose using the model-selection searching method for model-order selection, which we call partial-model order selection. We show by simulations that the proposed searching method gives better accuracies than the traditional one, especially for low signal-to-noise ratios over a wide range of model-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model-order selection criteria can be applied to find the optimal order. Some of the more commonly used information theoretic-based procedures include Akaike’s information criterion (AIC) [1], corrected Akaike (AICc) [2], minimum description length (MDL) [3], normalized maximum likelihood (NML) [4], Hannan-Quinn criterion (HQC) [5], conditional model-order estimation (CME) [6], and the efficient detection criterion (EDC) [7]. From a practical point of view, it is difficult to decide which model order selection criterion to use. Many of them perform reasonably well when the signal-to-noise ratio (SNR) is high. The discrepancies in their performance, however, become more evident when the SNR is low. In those situations, the performance of the given technique is not only determined by the model structure (say a polynomial trend versus a Fourier series) but, more importantly, by the relative values of the parameters within the model. This makes the comparison between the model-order selection algorithms difficult as within the same model with a given order one could find an example for which one of the methods performs favourably well or fails [6, 8]. Our aim is to improve the performance of the model order selection criteria in cases where the SNR is low by considering a model-selection searching procedure that takes into account not only the full-model order search but also a partial model order search within the given model order. Understandably, the improvement in the performance of the model order estimation is at the expense of additional computational complexity.

Model-order selection in Zernike polynomial expansion of corneal surfaces using the efficient detection criterion

Corneal-height data are typically measured with videokeratoscopes and modeled using a set of orthogonal Zernike polynomials. We address the estimation of the number of Zernike polynomials, which is formalized as a model-order selection problem in linear regression. Classical information-theoretic criteria tend to overestimate the corneal surface due to the weakness of their penalty functions, while bootstrap-based techniques tend to underestimate the surface or require extensive processing. In this paper, we propose to use the efficient detection criterion (EDC), which has the same general form of information-theoretic-based criteria, as an alternative to estimating the optimal number of Zernike polynomials. We first show, via simulations, that the EDC outperforms a large number of information-theoretic criteria and resampling-based techniques. We then illustrate that using the EDC for real corneas results in models that are in closer agreement with clinical expectations and provides means for distinguishing normal corneal surfaces from astigmatic and keratoconic surfaces.

Apoptosis is induced in Chlamydia trachomatis infected HEp-2 cells by the addition of a combination innate immune activation compounds and the inhibitor wedelolactone

Problem: Innate immune activation of human cells, for some intracellular pathogens, is advantageous for vacuole morphology and pathogenic viability. It is unknown whether innate immune activation is advantageous to Chlamydia trachomatis viability. ----- ----- Method of study: Innate immune activation of HEp-2 cells during Chlamydia infection was conducted using lipopolysaccharide (LPS), polyI:C, and wedelolactone (innate immune inhibitor) to investigate the impact of these conditions on viability of Chlamydia. ----- ----- Results: The addition of LPS and polyI:C to stimulate activation of the two distinct innate immune pathways (nuclear factor kappa beta and interferon regulatory factor) had no impact on the viability of Chlamydia. However, when compounds targeting either pathway were added in combination with the specific innate immune inhibitor (wedelolactone) a major impact on Chlamydia viability was observed. This impact was found to be due to the induction of apoptosis of the HEp-2 cells under these conditions. ----- ----- Conclusion: This is the first time that induction of apoptosis has been reported in C. trachomatis-infected cells when treated with a combination of innate immune activators and wedelolactone.

Par4 is a coactivator for a splice isoform-specific transcriptional activation domain in WT1

The Wilms’ tumor suppressor protein WT1 is a transcriptional regulator involved in differentiation and the regulation of cell growth. WT1 is subject to alternative splicing, one isoform including a 17–amino acid region that is specific to mammals. The function of this 17–amino acid insertion is not clear, however. Here, we describe a transcriptional activation domain in WT1 that is specific to the WT1 splice isoform that contains the 17–amino acid insertion. We show that the function of this domain in transcriptional activation is dependent on a specific interaction with the prostate apoptosis response factor par4. A mutation in WT1 found in Wilms’ tumor disturbs the interaction with par4 and disrupts the function of the activation domain. Analysis of WT1 derivatives in cells treated to induce par4 expression showed a strong correlation between the transcription function of the WT1 17–amino acid insertion and the ability of WT1 to regulate cell survival and proliferation. Our results provide a molecular mechanism by which alternative splicing of WT1 can regulate cell growth in development and disease.

Application of higher order statistics/spectra in biomedical signals : a review

For many decades correlation and power spectrum have been primary tools for digital signal processing applications in the biomedical area. The information contained in the power spectrum is essentially that of the autocorrelation sequence; which is sufficient for complete statistical descriptions of Gaussian signals of known means. However, there are practical situations where one needs to look beyond autocorrelation of a signal to extract information regarding deviation from Gaussianity and the presence of phase relations. Higher order spectra, also known as polyspectra, are spectral representations of higher order statistics, i.e. moments and cumulants of third order and beyond. HOS (higher order statistics or higher order spectra) can detect deviations from linearity, stationarity or Gaussianity in the signal. Most of the biomedical signals are non-linear, non-stationary and non-Gaussian in nature and therefore it can be more advantageous to analyze them with HOS compared to the use of second order correlations and power spectra. In this paper we have discussed the application of HOS for different bio-signals. HOS methods of analysis are explained using a typical heart rate variability (HRV) signal and applications to other signals are reviewed.

Order supported by law : the enforcement of norms in virtual communities

As online social spaces continue to grow in importance, the complex relationship between users and the private providers of the platforms continues to raise increasingly difficult questions about legitimacy in online governance. This article examines two issues that go to the core of egitimate governance in online communities: how are rules enforced and punishments imposed, and how should the law support legitimate governance and protect participants from the illegitimate exercise of power? Because the rules of online communities are generally ultimately backed by contractual terms of service, the imposition of punishment for the breach of internal rules exists in a difficult conceptual gap between criminal law and the predominantly compensatory remedies of contractual doctrine. When theorists have addressed the need for the rules of virtual communities to be enforced, a dichotomy has generally emerged between the appropriate role of criminal law for 'real' crimes, and the private, internal resolution of 'virtual' or 'fantasy' crimes. In this structure, the punitive effect of internal measures is downplayed and the harm that can be caused to participants by internal sanctions is systemically undervalued.

A new unequal DC link voltage configuration for a single phase multilevel converter to reduce low order harmonics

Multilevel converters are used in high power and high voltage applications due to their attractive benefits in generating high quality output voltage. Increasing the number of voltage levels can lead to a reduction in lower order harmonics. Various modulation and control techniques are introduced for multilevel converters like Space Vector Modulation (SVM), Sinusoidal Pulse Width Modulation (SPWM) and Harmonic Elimination (HE) methods. Multilevel converters may have a DC link with equal or unequal DC voltages. In this paper a new modulation technique based on harmonic elimination method is proposed for those multilevel converters that have unequal DC link voltages. This new technique has better effect on output voltage quality and less Total Harmonic Distortion (THD) than other modulation techniques. In order to verify the proposed modulation technique, MATLAB simulations are carried out for a single-phase diode-clamped inverter.