Isolation and characterization of charge-tagged phenylperoxyl radicals in the gas phase : direct evidence for products and pathways in low temperature benzene oxidation

The phenylperoxyl radical has long been accepted as a critical intermediate in the oxidation of benzene and an archetype for arylperoxyl radicals in combustion and atmospheric chemistry. Despite being central to many contemporary mechanisms underpinning these chemistries, reports of the direct detection or isolation of phenylperoxyl radicals are rare and there is little experimental evidence connecting this intermediate with expected product channels. We have prepared and isolated two charge-tagged phenyl radical models in the gas phase [i.e., 4-(N,N,N-trimethylammonium) phenyl radical cation and 4-carboxylatophenyl radical anion] and observed their reactions with dioxygen by ion-trap mass spectrometry. Measured reaction rates show good agreement with prior reports for the neutral system (k(2)[(Me3N+)C6H4 center dot + O-2] = 2.8 x 10(-11) cm(3) molecule(-1) s(-1), Phi = 4.9%; k(2)[(-O2C)C6H4 center dot + O-2] = 5.4 x 10(-1)1 cm(3) molecule(-1) s(-1), Phi = 9.2%) and the resulting mass spectra provide unequivocal evidence for the formation of phenylperoxyl radicals. Collisional activation of isolated phenylperoxyl radicals reveals unimolecular decomposition by three pathways: (i) loss of dioxygen to reform the initial phenyl radical; (ii) loss of atomic oxygen yielding a phenoxyl radical; and (iii) ejection of the formyl radical to give cyclopentadienone. Stable isotope labeling confirms these assignments. Quantum chemical calculations for both charge-tagged and neutral phenylperoxyl radicals confirm that loss of formyl radical is accessible both thermodynamically and entropically and competitive with direct loss of both hydrogen atom and carbon dioxide.

Are in vitro estimates of cell diffusivity and cell proliferation rate sensitive to assay geometry?

Cells respond to various biochemical and physical cues during wound–healing and tumour progression. In vitro assays used to study these processes are typically conducted in one particular geometry and it is unclear how the assay geometry affects the capacity of cell populations to spread, or whether the relevant mechanisms, such as cell motility and cell proliferation, are somehow sensitive to the geometry of the assay. In this work we use a circular barrier assay to characterise the spreading of cell populations in two different geometries. Assay 1 describes a tumour–like geometry where a cell population spreads outwards into an open space. Assay 2 describes a wound–like geometry where a cell population spreads inwards to close a void. We use a combination of discrete and continuum mathematical models and automated image processing methods to obtain independent estimates of the effective cell diffusivity, D, and the effective cell proliferation rate, λ. Using our parameterised mathematical model we confirm that our estimates of D and λ accurately predict the time–evolution of the location of the leading edge and the cell density profiles for both assay 1 and assay 2. Our work suggests that the effective cell diffusivity is up to 50% lower for assay 2 compared to assay 1, whereas the effective cell proliferation rate is up to 30% lower for assay 2 compared to assay 1.

Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation

Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Protocol : A highly sensitive RT-PCR method for detection and quantification of microRNAs

MicroRNAs (miRNAs) are a class of small non-coding RNAs with a critical role in development and environmental responses. Efficient and reliable detection of miRNAs is an essential step towards understanding their roles in specific cells and tissues. However, gel-based assays currently used to detect miRNAs are very limited in terms of throughput, sensitivity and specificity. Here we provide protocols for detection and quantification of miRNAs by RT-PCR. We describe an end-point and real-time looped RT-PCR procedure and demonstrate detection of miRNAs from as little as 20 pg of plant tissue total RNA and from total RNA isolated from as little as 0.1 l of phloem sap. In addition, we have developed an alternative real-time PCR assay that can further improve specificity when detecting low abundant miRNAs. Using this assay, we have demonstrated that miRNAs are differentially expressed in the phloem sap and the surrounding vascular tissue. This method enables fast, sensitive and specific miRNA expression profiling and is suitable for facilitation of high-throughput detection and quantification of miRNA expression.

Competitive charge-remote and anion-induced fragmentations of the non-8-enoate anion. A charge-remote reaction which co-occurs with hydrogen scrambling

The non-8-enoate anion undergoes losses of the elements of C3H6, C4H8 and C6H12 on collisional activation, The mechanisms of these processes have been elucidated by a combination of product ion and labelling (H-2 and C-13) studies, together with a neutralisation reionisation mass spectrometric study. These studies allow the following conclusions to be made. (i) The loss of C3H6 involves cyclisation of the enolate anion of non-8-enoic acid to yield the cyclopentyl carboxylate anion and propene. (ii) The loss of 'C4H8' is a charge-remote process (one which proceeds remote from the charged centre) which yields the pent-4-enoate anion, butadiene and dihydrogen. This process co-occurs and competes with complex H scrambling. (iii) The major loss of 'C6H12' occurs primarily by a charge-remote process yielding the acrylate anion, hexa-1,5-diene and dihydrogen, but in this case no H scrambling accompanies the process. (iv) It is argued that the major reason why the two charge-remote processes occur in preference to anion-induced losses of but-l-ene and hex-l-ene from the respective 4- and 2-anions is that although these anions are formed, they have alternative and lower energy fragmentation pathways than those involving the losses of but-l-ene and hex-l-ene; viz. the transient 4-anion undergoes facile proton transfer to yield a more stable anion, whereas the 2-(enolate) anion undergoes preferential cyclisation followed by elimination of propene [see (i) above].

Ultra sensitive label free surface enhanced Raman spectroscopy method for the detection of biomolecules

We present a proof of concept for a novel nanosensor for the detection of ultra-trace amounts of bio-active molecules in complex matrices. The nanosensor is comprised of gold nanoparticles with an ultra-thin silica shell and antibody surface attachment, which allows for the immobilization and direct detection of bio-active molecules by surface enhanced Raman spectroscopy (SERS) without requiring a Raman label. The ultra-thin passive layer (~1.3 nm thickness) prevents competing molecules from binding non-selectively to the gold surface without compromising the signal enhancement. The antibodies attached on the surface of the nanoparticles selectively bind to the target molecule with high affinity. The interaction between the nanosensor and the target analyte result in conformational rearrangements of the antibody binding sites, leading to significant changes in the surface enhanced Raman spectra of the nanoparticles when compared to the spectra of the un-reacted nanoparticles. Nanosensors of this design targeting the bio-active compounds erythropoietin and caffeine were able to detect ultra-trace amounts the analyte to the lower quantification limits of 3.5×10−13 M and 1×10−9 M, respectively.

Nanoherding : plasma-chemical synthesis and electric-charge-driven self organization of SiO2 nanodots

We report on the chemical synthesis of the arrays of silicon oxide nanodots and their self-organization on the surface via physical processes triggered by surface charges. The method based on chemically active oxygen plasma leads to the rearrangement of nanostructures and eventually to the formation of groups of nanodots. This behavior is explained in terms of the effect of electric field on the kinetics of surface processes. The direct measurements of the electric charges on the surface demonstrate that the charge correlates with the density and arrangement of nanodots within the array. Extensive numerical simulations support the proposed mechanism and prove a critical role of the electric charges in the self-organization. This simple and environment-friendly self-guided process could be used in the chemical synthesis of large arrays of nanodots on semiconducting surfaces for a variety of applications in catalysis, energy conversion and storage, photochemistry, environmental and biosensing, and several others.

Highly NO2 sensitive caesium doped graphene oxide conductometric sensors

Here we report on the synthesis of caesium doped graphene oxide (GO-Cs) and its application to the development of a novel NO2 gas sensor. The GO, synthesized by oxidation of graphite through chemical treatment, was doped with Cs by thermal solid-state reaction. The samples, dispersed in DI water by sonication, have been drop-casted on standard interdigitated Pt electrodes. The response of both pristine and Cs doped GO to NO2 at room temperature is studied by varying the gas concentration. The developed GO-Cs sensor shows a higher response to NO2 than the pristine GO based sensor due to the oxygen functional groups. The detection limit measured with GO-Cs sensor is ≈90 ppb.

Equilibrium and relaxation of particulate charge in fluorocarbon plasmas

Charging of micron-size particulates, often appearing in fluorocarbon plasma etching experiments, is considered. It is shown that in inductively coupled and microwave slot-excited plasmas of C4F8 and Ar gas mixtures, the equilibrium particle charge and charge relaxation processes are controlled by a combination of microscopic electron, atomic (Ar+ and F+), and molecular ion (CF+ 3, CF+ 2, and CF+) currents. The impact of molecular ion currents on the particulate charging and charge relaxation processes is analyzed. It is revealed that in low-power (<0.5 kW) microwave slot-excited plasmas, the impact of the combined molecular ion current to the total positive microscopic current on the particle can be as high as 40%. The particulate charge relaxation rate in fluorocarbon plasmas appears to exceed 108 s-1, which is almost one order of magnitude higher than that from purely argon plasmas. This can be attributed to the impact of positive currents of fluorocarbon molecular ions, as well as to the electron density fluctuations with particle charge, associated with electron capture and release by the particulates.

A control theoretic paradigm for cell signaling networks : a simple complexity for a sensitive robustness

The fields of molecular biology and cell biology are being flooded with complex genomic and proteomic datasets of large dimensions. We now recognize that each molecule in the cell and tissue can no longer be viewed as an isolated entity. Instead, each molecule must be considered as one member of an interacting network. Consequently, there is an urgent need for mathematical models to understand the behavior of cell signaling networks in health and in disease.

Dust charge and ion drag forces in a high-voltage, capacitive radio frequency sheath

The charge of an isolated dust grain and ion drag forces on the grain in a collisionless, high-voltage, capacitive rf sheath are studied theoretically. The studies are carried out assuming that the positive ions are monoenergetic, as well as in more realistic approximation, assuming that the time-averaged energy distribution of ions impinging on the dust grain has a double-peaked hollow profile. For the nonmonoenergetic case, an analytical expression for the ion flux to the dust grain is obtained. It is studied how the dust charge and ion drag forces depend on the rf frequency, electron density at plasma-sheath boundary, electron temperature and ratio of the effective oscillation amplitude of rf current to the electron Debye length. It is shown that the dust charge and ion drag forces obtained in the monoenergetic ion approximation may differ from those calculated assuming that the ions are nonmonoenergetic. The difference increases with increasing the width of the ion energy spread in the ion distribution. © 2009 American Institute of Physics.

Evolution of Langmuir waves in a plasma contaminated by variable-charge impurities

The propagation of Langmuir waves in nonisothermal plasmas contaminated by fine dust particles with variable charge is investigated for a self-consistent closed system. Dust charge relaxation, ionization, recombination, and collisional dissipation are taken into account. It is shown that the otherwise unstable coupling of the Langmuir and dust-charge relaxation modes becomes stable and the Langmuir waves are frequency down-shifted.

Tailoring of ion species composition in complex plasmas with charge exchange collisions

A generic approach towards tailoring of ion species composition in reactive plasmas used for nanofabrication of various functional nanofilms and nanoassemblies, based on a simplified model of a parallel-plate rf discharge, is proposed. The model includes an idealized reactive plasma containing two neutral and two ionic species interacting via charge exchange collisions in the presence of a microdispersed solid component. It is shown that the number densities of the desired ionic species can be efficiently managed by adjusting the dilution of the working gas in a buffer gas, rates of electron impact ionization, losses of plasma species on the discharge walls, and surfaces of fine particles, charge exchange rates, and efficiency of three-body recombination processes in the plasma bulk. The results are relevant to the plasma-aided nanomanufacturing of ordered patterns of carbon nanotip and nanopyramid microemitters.

Low-frequency dispersion properties of plasmas with variable-charge impurities

A theory of low-frequency dust-acoustic waves in low-temperature collisional plasmas containing variable-charge impurities is presented. Physical processes such as dust-charge relaxation, ionization-recombination of the electrons and ions, electron and ion elastic collisions with neutrals and dusts, as well as charging collisions with the dusts, are taken into account. Inclusion of these processes allows a balance of the plasma particles and thus a self-consistent determination of the stationary state of the unperturbed plasma. The generalized dispersion relation describing the propagation and damping of the dust acoustic waves is derived and analyzed. © 2000 American Institute of Physics.

Audit fees and asset securitization risks

The thesis investigates “where were the auditors in asset securitizations”, a criticism of the audit profession before and after the onset of the global financial crisis (GFC). Asset securitizations increase audit complexity and audit risks, which are expected to increase audit fees. Using US bank holding company data from 2003 to 2009, this study examines the association between asset securitization risks and audit fees, and its changes during the global financial crisis. The main test is based on an ordinary least squares (OLS) model, which is adapted from the Fields et al. (2004) bank audit fee model. I employ a principal components analysis to address high correlations among asset securitization risks. Individual securitization risks are also separately tested. A suite of sensitivity tests indicate the results are robust. These include model alterations, sample variations, further controls in the tests, and correcting for the securitizer self-selection problem. A partial least squares (PLS) path modelling methodology is introduced as a separate test, which allows for high intercorrelations, self-selection correction, and sequential order hypotheses in one simultaneous model. The PLS results are consistent with the main results. The study finds significant and positive associations between securitization risks and audit fees. After the commencement of the global financial crisis in 2007, there was an increased focus on the role of audits on asset securitization risks resulting from bank failures; therefore I expect that auditors would become more sensitive to bank asset securitization risks after the commencement of the crisis. I find that auditors appear to focus on different aspects of asset securitization risks during the crisis and that auditors appear to charge a GFC premium for banks. Overall, the results support the view that auditors consider asset securitization risks and market changes, and adjust their audit effort and risk considerations accordingly.