Distinguishing nanomaterial particles from background airborne particulate matter for quantitative exposure assessment

As the production of engineered nanomaterials quantitatively expands, the chance that workers involved in the manufacturing process will be exposed to nanoparticles also increases. A risk management system is needed for workplaces in the nanomaterial industry based on the precautionary principle. One of the problems in the risk management system is difficulty of exposure assessment. In this article, examples of exposure assessment in nanomaterial industries are reviewed with a focus on distinguishing engineered nanomaterial particles from background nanoparticles in workplace atmosphere. An approach by JNIOSH (Japan National Institute of Occupational Safety and Health) to quantitatively measure exposure to carbonaceous nanomaterials is also introduced. In addition to real-time measurements and qualitative analysis by electron microscopy, quantitative chemical analysis is necessary for quantitatively assessing exposure to nanomaterials. Chemical analysis is suitable for quantitative exposure measurement especially at facilities with high levels of background NPs.     

Autocorrelation function formulations and the turbulence dissipation rate: Application to dispersion models

The classical statistical diffusion theory and the binomial autocorrelation function are used to obtain a new formulation for the turbulence dissipation rate ε. The approach employs the Maclaurin series expansion of a logarithm function contained in the dispersion parameter formulation. The numerical coefficient of this new relation for ε is 100% larger than the numerical coefficient of the classical relation derived from the exponential autocorrelation function. A similar approach shows that the dispersion parameter obtained from the even exponential autocorrelation function does not result in a relation for ε and, therefore, is not suitable for application in dispersion models. In addition, a statistical comparison to experimental ground-level concentration data demonstrates that this newly derived relation for ε as well as other formulations for the turbulence dissipation rate are suitable for application in Lagrangian stochastic dispersion models. Therefore, the analysis shows that there is an uncertainty regarding the turbulence dissipation rate function form and the autocorrelation function form.     

Long-range correlations in time series generated by time-fractional diffusion: A numerical study

Time series models showing power law tails in autocorrelation functions are common in econometrics. A special non-Markovian model for such kind of time series is provided by the random walk introduced by Gorenflo et al. as a discretization of time fractional diffusion. The time series so obtained are analyzed here from a numerical point of view in terms of autocorrelations and covariance matrices.     

A statistical assessment of ambient electromagnetic field using body-worn multiaxial sensors

The electromagnetic field exposure of the population due to wireless communications originates from both down-link and up-link emissions. Although the main contribution comes generally from the latter (e.g., higher by three to five orders of magnitude for the 2G), the former must be considered as well, because they are continual, and as contributions can be competitive for some cases (e.g., in femtocells). Sensor and exposimeter networks (NW) can be deployed by the operators themselves (to enrich feedback information from their own NW) or by independent external stakeholders such as regulatory agencies or local authorities. When sensors are directly worn by a user, body proximity effects – notably the masking effect – can introduce significant errors in the ambient field measurement. A methodology of the statistical assessment of this harmful effect is proposed in this article. It is mainly based on electromagnetic simulations (and partly on measurements) of a triaxial sensor – composed of three orthogonal wideband probes devoted to the evaluation of the field components – placed at different positions of a set of whole body phantoms. The main original contribution of the proposed approach is that both the isolated sensor calibration procedure and the assessment of the measurement errors are based on statistical analyses accounting for the propagation environment. The quantitative results are obtained using statistical channel models for polarimetric and non-polarimetric measurements in various propagation scenarios. Some quantitative results examples are presented. Eventually, preliminary corrections schemes are proposed.     

Wavelet-modified fringe-adjusted joint transform correlator

In this paper, we implement a wavelet-modified fringe-adjusted joint transform correlator (JTC) for real-time target recognition applications. In real-time situation the input scene is captured using a charge-coupled device (CCD) camera. The obtained joint power spectrum is multiplied by a pre-synthesized fringe-adjusted filter and the resultant function is processed with an appropriately scaled wavelet filter. Three performance measure parameters: correlation peak intensity, peak-to-sidelobe ratio, and signal-to-clutter ratio have been calculated for fringe-adjusted joint transform correlator (FJTC) and wavelet-modified fringe-adjusted joint transform correlator (WFJTC). The WFJTC has been found to yield better results in comparison to conventional FJTC. To suppress the undesired strong dc, the resultant function is differentiated. Differential processing wavelet-modified fringe-adjusted joint power spectrum removes the zero-order spectra and hence improves the detection efficiency. To focus the correlation terms in different planes in order to capture one of the desired autocorrelation peaks and discard the strong dc and another autocorrelation peak, chirp-encoding technique has also been applied. Targets with Gaussian and speckle noise have also been used to check the correlation outputs. Computer simulation and experimental results are presented.     

Real-time chirp diagnostic for ultrashort laser pulses

Using a real-time Fourier-transform algorithm, we present a simple technique for measuring the chirp of femtosecond laser pulses. We demonstrate significantly enhanced sensitivity compared with standard autocorrelation measurements.     

Autoregressive conditional duration as a model for financial market crashes prediction

There is an increasing number of studies showing that financial market crashes can be detected and predicted. The main aim of the research was to develop a technique for crashes prediction based on the analysis of durations between sequent crashes of a certain magnitude of Dow Jones Industrial Average. We have found significant autocorrelation in the series of durations between sequent crashes and suggest autoregressive conditional duration models (ACD) to forecast the crashes. We apply the rolling intervals technique in the sample of more than 400 DJIA crashes in 1896–2011 and repeatedly use the data on 100 sequent crashes to estimate a family of ACD models and calculate forecasts of the one following crash. It appears that the ACD models provide significant predictive power when combined with the inter-event waiting time technique. This suggests that despite the high quality of retrospective predictions, using the technique for real-time forecasting seems rather ineffective, as in the case of every particular crash the specification of the ACD model, which would provide the best quality prediction, is rather hard to identify.     

Measurements and inverse calculations of spectral radiation intensities of a turbulent ethylene/air jet flame

Fast (6250 Hz) line-of-sight measurements of infrared spectral radiation intensities (I_λ) from a luminous flame and a new deconvolution technique for the estimate of local scalar properties using inverse radiation calculations are reported. Time series data of I_λ for one diametric and nine chord-like radiation paths in a representative horizontal plane were measured. Statistical properties of I_λ, including mean, root mean square (rms), probability density function, autocorrelation coefficient, and power spectral density, were obtained from the time series data. The measured statistical properties of I_λ at two representative wavelengths, which are dominated by carbon dioxide (CO₂) and soot radiation, respectively, are reported. The autocorrelation coefficient data show large negative loops with repeatable zero crossings at 20 ms and minimum values as low as −0.2 at 30–40 ms. Radial distributions of mean and rms CO₂ mole fractions and temperatures were estimated using inverse calculations of mean I_λ at two different wavelengths dominated by CO₂ radiation in conjunction with the relationship of these quantities to mixture fractions. Soot volume fraction distributions were also estimated using inverse calculations of mean I_λ at a wavelength dominated by continuum soot radiation. The estimated local mixture fraction distributions were in reasonably good agreement with sampling data from similar flames. The calculated mean I_λ from 1.4 to 4.8 μm other than those used in the inverse calculations matched the experimental data well. The present method provides non-intrusive measurements of major gas species and temperature statistics in turbulent soot containing flames not accessible to other optical diagnostics.     

On a conjecture of Alley and Alder for fluids and Lorentz models

We discuss a conjecture of Alley and Alder predicting a relation between the four-point and the two-point velocity autocorrelation functions for fluids and Lorentz models at sufficiently long times. If the conjecture is correct a modified Burnett coefficient can be defined, which has a finite value, contrary to the ordinary Burnett coefficient, which is divergent. The conjecture is tested for four classes of models with different methods: for three-dimensional fluids mode-coupling theory yields a negative result. The conjecture is confirmed for thed-dimensional deterministic Lorentz gas (d 2) and for a class ofd-dimensional stochastic Lorentz models (d 1) by low-density kinetic theory, as well as by rigorous results, available for one dimension. For yet another class of one-dimensional stochastic Lorentz models, which are exactly solvable in one dimension, the result is negative again. All four classes of models show long-time tails in the velocity autocorrelation function and have a finite diffusion coefficient.     

Autocorrelation measurement of 6-fs pulses based on the two-photon-induced photocurrent in a GaAsP photodiode

We experimentally characterize the two-photon response of a GaAsP photodiode by use of a femtosecond Ti:sapphire laser tuned below the diode bandgap. The photodiode is shown to be highly suitable for real-time second-order autocorrelation measurements of pulses as short as 6fs in duration and with energies as small as a few picojoules.     

The mutual interaction of molecular rotation and translation

The dynamics of molecular rototranslation are treated with an equation of motion with a non-Markovian, stochastic force/torque. It is shown that this Mori/Kubo/Zwanzig representation is equivalent to a multidimensional Markov equation which may be identified with analytical models of the molecular motion. Langevin and Fokker-Planck equations for two such models are derived from the general equations of motion. The analytical results are compared with a computer simulation of the velocity/angular velocity mixed autocorrelation function, C _vω(t) = <v(0) . ω(t)> for a triatomic of C _2v symmetry.     

First and second order semi-Markov chains for wind speed modeling

The increasing interest in renewable energy, particularly in wind, has given rise to the necessity of accurate models for the generation of good synthetic wind speed data. Markov chains are often used for this purpose but better models are needed to reproduce the statistical properties of wind speed data. We downloaded a database, freely available from the web, in which are included wind speed data taken from L.S.I. -Lastem station (Italy) and sampled every 10 min. With the aim of reproducing the statistical properties of this data we propose the use of three semi-Markov models. We generate synthetic time series for wind speed by means of Monte Carlo simulations. The time lagged autocorrelation is then used to compare statistical properties of the proposed models with those of real data and also with a synthetic time series generated through a simple Markov chain.     

Tuning the dipole-directed assembly of core-shell nickel-coated gold nanorods

The aim of this paper is to describe the process and challenges in building exposure scenarios for engineered nanomaterials (ENM), using an exposure scenario format similar to that used for the European Chemicals regulation (REACH). Over 60 exposure scenarios were developed based on information from publicly available sources (literature, books, and reports), publicly available exposure estimation models, occupational sampling campaign data from partnering institutions, and industrial partners regarding their own facilities. The primary focus was on carbon-based nanomaterials, nano-silver (nano-Ag) and nano-titanium dioxide (nano-TiO₂), and included occupational and consumer uses of these materials with consideration of the associated environmental release. The process of building exposure scenarios illustrated the availability and limitations of existing information and exposure assessment tools for characterizing exposure to ENM, particularly as it relates to risk assessment. This article describes the gaps in the information reviewed, recommends future areas of ENM exposure research, and proposes types of information that should, at a minimum, be included when reporting the results of such research, so that the information is useful in a wider context.     

Critical dynamics of cluster algorithms in the dilute Ising model

Autocorrelation times for thermodynamic quantities atT _C are calculated from Monte Carlo simulations of the site-diluted simple cubic Ising model, using the Swendsen-Wang and Wolff cluster algorithms. Our results show that for these algorithms the autocorrelation timesdecrease when reducing the concentration of magnetic sites from 100% down to 40%. This is of crucial importance when estimating static properties of the model, since the variances of these estimators increase with autocorrelation time. The dynamical critical exponents are calculated for both algorithms, observing pronounced finite-size effects in the energy autocorrelation data for the algorithm of Wolff. We conclude that, when applied to the dilute Ising model, cluster algorithms become even more effective than local algorithms, for whichincreasing autocorrelation times are expected.     

Measuring inter-pulse intervals in sperm whale clicks: consistency of automatic estimation methods

Sperm whale clicks are characterized by a multi-pulsed structure. The time lag between consecutive pulses, i.e., the inter-pulse interval (IPI), is related to the size of the sound production organ such that its measurement provides a means to acoustically estimate the size of individual whales. Due to off-axis effects the identification of pulses is, however, not always straightforward, and automatic measurement methods provide not only more objective estimation, but may also facilitate IPI estimation in cases where single click measurements are ambiguous. In particular, averaging measurements over a time series of clicks from the same whale could enhance the discrimination of time invariant pulses. The authors developed two automatic methods of automatic IPI measurement based on waveform and autocorrelation averaging and compared their accuracy and consistency with other previously used methods. Manual measurement by an experienced operator provided the most self-consistent estimates. The autocorrelation averaging technique had the best overall performance of the automated methods achieving a very similar performance to manual measurement. On some recordings cepstrum averaging methods converged when autocorrelation did not. Therefore, applying both of these automated methods and choosing the best of the two are recommended.     

Portable X-Ray Fluorescence as a Rapid Technique for Surveying Elemental Distributions in Soil

Case studies from two sites demonstrate how concentration distributions of hazardous contaminants can be rapidly measured and visualized using portable XRF (X-ray fluorescence) coupled with geostatistical interpolation tools. In this study, lead is used as an exemplar due to its well-known detrimental effect on human health through long-term exposure. A portable Thermo Scientific NITON X-ray fluorescence (XRF) instrument was used for real-time in-situ concentration measurements, which were linked to GPS coordinates of the sampling locations. A 52 point mixed sampling density survey was performed at a site near Maynooth, Co. Kildare, and a second 58 survey undertaken at Dublin City University (DCU). At Maynooth, high concentrations of Pb (above 110 mg/kg) were found close to the site where a local canal meets a road. At the DCU site, results indicate high Pb concentrations (above 160 mg/kg) near a busy main road. Geostatistical techniques were used to generate concentration prediction and critical threshold contour surfaces for both sites. Linked with GPS coordinates for each sampling location, this technology enables the distribution of multiple elements to be mapped over wide areas in a relatively short time. Supplemental materials are available for this article. Go to the publisher's online edition of Spectroscopy Letters to view the supplemental file.     

A new estimator method for GARCH models

The GARCH (p, q) model is a very interesting stochastic process with widespread applications and a central role in empirical finance. The Markovian GARCH (1, 1) model has only 3 control parameters and a much discussed question is how to estimate them when a series of some financial asset is given. Besides the maximum likelihood estimator technique, there is another method which uses the variance, the kurtosis and the autocorrelation time to determine them. We propose here to use the standardized 6th moment. The set of parameters obtained in this way produces a very good probability density function and a much better time autocorrelation function. This is true for both studied indexes: NYSE Composite and FTSE 100. The probability of return to the origin is investigated at different time horizons for both Gaussian and Laplacian GARCH models. In spite of the fact that these models show almost identical performances with respect to the final probability density function and to the time autocorrelation function, their scaling properties are, however, very different. The Laplacian GARCH model gives a better scaling exponent for the NYSE time series, whereas the Gaussian dynamics fits better the FTSE scaling exponent.     

Laser light scattering technique for non-invasive<Emphasis Type="Italic">in situ</Emphasis> simultaneous measurements on elastic constants and viscosity coefficients of nematic liquid crystals

The laser light scattering technique for non-invasivein situ simultaneous measurements on elastic constants and viscosity coefficients of nematic liquid crystals is introduced. By measuring the autocorrelation function of the scattered light from nematic liquid crystals at different scattering angles, the splay and twist elastic constantsK ₁₁ andK ₂₂ are obtained from the amplitudes of the autocorrelation function, and the viscosity coefficients ofη _Splay andη _Twist are determined using the viscoelastic ratiosK ₁₁/η _Splay andK ₂₂ η _Twist from the telaxation parameters of the two modes.     

Cycloparaphenylene (CPP) series are molecular models for graphene armchair edges: trends in their aromaticity and cyclic conjugation are evaluated

Cycloparaphenylene ([r]CPP) and cyclacene ([r]CA) series are models for short carbon nanotubes. It is shown that armchair edges in model cycloparaphenylenes possess greater aromaticity and cyclic conjugation than do zigzag edges in model cyclacenes. According to Aihara’s bond resonance energy (BRE) and Bosanac and Gutman energy effect (ef) measurements, cycloparaphenylenes are twice as aromatic as cyclacenes. The general solution of all eigenvalues of all members of the cycloparaphenylene series is given. The origin of the recurrence of some eigenvalues are determined.     

Onset of Lasing in Small Devices: The Identification of the First Threshold through Autocorrelation Resonance

A simple technique for identifying the onset of coherent emission in mesoscale lasers, which makes use of a small‐amplitude modulation added to the pump, is introduced. The optimal modulation frequency is obtained from the radio‐frequency power spectrum of the unperturbed laser emission. The identification of the lasing onset rests on the appearance of a resonance in the experimentally measured zero‐order autocorrelation function (g⁽²⁾(0)) plotted as a function of the pump rate. Numerical proof is provided in support of the autocorrelation resonance. The intrinsic simplicity of this technique and its inherent compatibility with photon counting makes it an excellent tool for certifying the onset of laser emission independent of the laser cavity volume. Recently published measurements of g⁽²⁾(0), obtained in nanolasers, support the extension of this technique to nanoscale devices.