Near-field Sources Research Articles

High-throughput in-silico prediction of ionization equilibria for pharmacokinetic modeling

Chemical ionization plays an important role in many aspects of pharmacokinetic (PK) processes such as protein binding, tissue partitioning, and apparent volume of distribution at steady state (Vdss). Here, estimates of ionization equilibrium constants (i.e., pKa) were analyzed for 8132 pharmaceuticals and 24,281 other compounds to which humans might be exposed in the environment. Results revealed broad differences in the ionization of pharmaceutical chemicals and chemicals with either near-field (in the home) or far-field sources. The utility of these high-throughput ionization predictions was evaluated via a case-study of predicted PK Vdss for 22 compounds monitored in the blood and serum of the U.S. population by the U.S. Centers for Disease Control and Prevention National Health and Nutrition Examination Survey (NHANES). The chemical distribution ratio between water and tissue was estimated using predicted ionization states characterized by pKa. Probability distributions corresponding to ionizable atom types (IATs) were then used to analyze the sensitivity of predicted Vdss on predicted pKa using Monte Carlo methods. 8 of the 22 compounds were predicted to be ionizable. For 5 of the 8 the predictions based upon ionization are significantly different from what would be predicted for a neutral compound. For all but one (foramsulfuron), the probability distribution of predicted Vdss generated by IAT sensitivity analysis spans both the neutral prediction and the prediction using ionization. As new data sets of chemical-specific information on metabolism and excretion for hundreds of chemicals are being made available (e.g., Wetmore et al., 2015), high-throughput methods for calculating Vdss and tissue-specific PK distribution coefficients will allow the rapid construction of PK models to provide context for both biomonitoring data and high-throughput toxicity screening studies such as Tox21 and ToxCast.

Classification and localization of mixed near-field and far-field sources using mixed-order statistics

In this paper, a novel algorithm based on mixed-order statistics is proposed for mixed near-field and far-field source localization. Firstly, the direction-of-arrivals (DOAs) of far-field signals are estimated using the conventional MUSIC method based on second-order statistics. Then, a special fourth-order cumulant matrix of the array output is constructed, which is only related to DOA parameters of mixed sources. After estimating the kurtosis of far-field signals, the related far-field components can be removed from the constructed cumulant matrix and the near-field components can be derived. With the near-field data in the cumulant domain, the DOA estimations of near-field sources can be performed using high-order MUSIC spectrum. Finally, with the near-field DOA estimates, the range parameters of near-field sources can be obtained via one-dimensional search. The proposed algorithm involves neither two-dimensional search nor additional parameter pairing processing. Moreover, it can achieve a more reasonable classification of the source types. Simulations results demonstrate the advantages of the proposed algorithm in comparison to the existing methods.

Performance enhancement of approximated model based near‐field sources localisation techniques

Most of the existing near-field sources localisation methods are based on an approximated model. Making use of such an approximation brings degradation in the estimation accuracy. In this study, the authors propose a correction method to mitigate this problem and improve the estimation performance of the approximated model based methods. Simulation results show that the proposed technique can significantly improve the performance of the classical approximated model based near-field sources localisation methods.

Electron-beam excited photon emission from monopole modes of a plasmonic nano-disc.

Plasmonic dark modes are not easy to be observed in the far field due to their weak photon emission. By contrast, it has been shown that a dark mode can be excited effectively by a near-field source such as an electron beam. In this Letter, we show theoretically that the photon emission from the monopole-like dark mode supported on a plasmonic nano-disc could be unexpectedly strong when excited by an electron beam through its hole. Even though this monopole mode is considered to be dark, it is found that the emission can be even "brighter" than the dipolar bright modes when the electron speed is higher than 0.6c. Due to the high conversion efficiency from electron energy loss to photon energy, the results could also suggest an optical method for the detection of high-energy electrons passing through the hole with negligible changes in electron speed.

Tsunami Detection by High Frequency Radar Beyond the Continental Shelf: II. Extension of Time Correlation Algorithm and Validation on Realistic Case Studies

In past work, tsunami detection algorithms (TDAs) have been proposed, and successfully applied to offline tsunami detection, based on analyzing tsunami currents inverted from high-frequency (HF) radar Doppler spectra. With this method, however, the detection of small and short-lived tsunami currents in the most distant radar ranges is challenging due to conflicting requirements on the Doppler spectra integration time and resolution. To circumvent this issue, in Part I of this work, we proposed an alternative TDA, referred to as time correlation (TC) TDA, that does not require inverting currents, but instead detects changes in patterns of correlations of radar signal time series measured in pairs of cells located along the main directions of tsunami propagation (predicted by geometric optics theory); such correlations can be maximized when one signal is time-shifted by the pre-computed long wave propagation time. We initially validated the TC-TDA based on numerical simulations of idealized tsunamis in a simplified geometry. Here, we further develop, extend, and apply the TC algorithm to more realistic tsunami case studies. These are performed in the area West of Vancouver Island, BC, where Ocean Networks Canada recently deployed a HF radar (in Tofino, BC), to detect tsunamis from far- and near-field sources, up to a 110 km range. Two case studies are considered, both simulated using long wave models (1) a far-field seismic, and (2) a near-field landslide, tsunami. Pending the availability of radar data, a radar signal simulator is parameterized for the Tofino HF radar characteristics, in particular its signal-to-noise ratio with range, and combined with the simulated tsunami currents to produce realistic time series of backscattered radar signal from a dense grid of cells. Numerical experiments show that the arrival of a tsunami causes a clear change in radar signal correlation patterns, even at the most distant ranges beyond the continental shelf, thus making an early tsunami detection possible with the TC-TDA. Based on these results, we discuss how the new algorithm could be combined with standard methods proposed earlier, based on a Doppler analysis, to develop a new tsunami detection system based on HF radar data, that could increase warning time. This will be the object of future work, which will be based on actual, rather than simulated, radar data.

Crustal Seismic Anisotropy in Shandong

Based on the seismic data of near-field source from Shandong Seismic Network, the study obtained the shear-wave splitting parameters from multiple stations. The results show that dominant directions of polarizations of fast shear-waves reflect the spatial distribution characteristics of tectonic stress in this area, CHD and LIS stations show 2 dominant direction, it reveals that the crustal seismic anisotropy in Shandong area is constrained by regional stress background, local failure and structure.

A Sequential Optimization Calibration Algorithm for Near-Field Source Localization.

This paper considers the near-field source location problem for a nonuniform linear array (non-ULA) in the presence of sensor gain and phase errors. A sequential optimization calibration method is proposed to simultaneously estimate the gain and phase errors as well as the locations of calibration sources involving the ranges and the azimuths by exploiting some imprecise a-priori knowledge of calibration sources. At each iteration of the proposed method, the source locations, and the gain and phase errors are obtained iteratively. Finally, at the analysis stage, we evaluate the effectiveness of the proposed technique using some numerical simulations. Results show that the proposed algorithm shares the capability to jointly estimate the source locations and the errors.

Passive Localization for Mixed Near-Field and Far-Field Sources Based on Cumulant Sparse Representation

Passive Localization for Mixed Near-Field and Far-Field Sources Based on Cumulant Sparse Representation

Source characterisation by mixing long-running tsunami wave numerical simulations and historical observations within a metamodel-aided ABC setting

Uncertainty related to the source parameters of earthquake can largely impact the tsunami-induced wave characteristics, especially in the case of near-field tsunami source. The combination of numerical simulations and historical eyewitness accounts can be used to better constrain those uncertainties. In the present study, we propose a Bayesian procedure to infer (i.e. learn) the probability distribution of the source parameters of the earthquake. The strategy is based on the combination of: (1) kriging-based metamodelling techniques to overcome the high computation time cost of the numerical simulator; and (2) Approximate Bayesian Computation (ABC) procedure to perform the Bayesian inference. The procedure is applied to the Ligurian (North West of Italy) 1887 tsunami case, for which tsunami-induced sea surface elevations at the coast have been reported at four locations, namely Marseille, Imperia, Diano-Marina and Genoa. The kriging metamodels are trained using only 300 long-running numerical simulations that were performed using the FUNWAVE-TVD code. Contrary to recent inversion exercises that can benefit from current modern observation networks (like tide gauges, sea bottom pressure gauges, GPS-mounted buoys), the case of historical tsunami like Liguria is complicated by the imprecision and scarcity of the observations: this is accounted for by conducting the combined ABC-kriging procedure a large number of times (i.e. 1000); each time a new set of observations being randomly generated to account for this observational error. The combined analysis of the inference results and of the observation uncertainty reveals that: (1) the coseismic slip is the most important source parameter with a very peaky density distribution around low values ranging from 0.3 to 0.6 m; (2) The fault width has a peaky density distribution around low values ranging from 10 to 12 km; (3) The rake and azimuth distribution only slightly deviate from the uniform prior, hence indicating a low influence of those parameters; (4) The bi-modal distribution of the dip is also evidenced.

Subspace-based Localization Approach for Near-field Source in Impulse Noise Environment

In this paper, we propose a subspace-based matching (SBM) approach based on fractional lower order moment (FLOM) matrix to estimate the location of near-field acoustic signals in additive nonGaussian impulsive noise environment. By matching the subspace in the fingerprint database and the subspace computed from the current received signals, we associate the received signal with its transmission location with high accuracy. The proposed algorithm has two advantages: firstly, it can locate multiple sources without estimating bearing and range of sources. Secondly, it is more robust to multipath, environment changing and noise level. The simulation results show the efficacy of our proposed algorithm.

An Exact Model-Based Method for Near-Field Sources Localization with Bistatic MIMO System.

In this paper, we propose an exact model-based method for near-field sources localization with a bistatic multiple input, multiple output (MIMO) radar system, and compare it with an approximated model-based method. The aim of this paper is to propose an efficient way to use the exact model of the received signals of near-field sources in order to eliminate the systematic error introduced by the use of approximated model in most existing near-field sources localization techniques. The proposed method uses parallel factor (PARAFAC) decomposition to deal with the exact model. Thanks to the exact model, the proposed method has better precision and resolution than the compared approximated model-based method. The simulation results show the performance of the proposed method.

Relative positioning method for near-field beam spot array with optical microscope image of lithographic patterns using linear regression

A method for simply analyzing the relation between spot positions of near-field beam sources with micrometer pitch is proposed using an optical microscope. Based on the locations of spots in an optical microscopy image of lithographic patterns, the effective relative position is derived using simple linear regression. Numerical analysis is performed to introduce the concept and to evaluate the methodology with random noise. The accuracy and uncertainty of the proposed method are discussed. To confirm the method’s feasibility, the experiments are conducted using fabricated probe array, and the experimental and numerical results are compared on the basis of uncertainty. An arbitrary pattern is recorded with respect to relative coordinates obtained based on the effective positions. We suggest a simple strategy for controlling beam spot array locations for pattern design in near-field lithography with less than 5-nm uncertainty.

Unambiguous Parameter Estimation of Multiple Near-Field Sources via Rotating Uniform Circular Array

Near-field source localization suffers from serious phase ambiguity, when the array aperture is larger than half-wavelength. In this letter, by performing adaptive rotation of uniform circular array with a center sensor, a closed-form algorithm based on phase difference is improved for estimating the source's three-dimensional (3-D) location (azimuth angle, elevation angle, and range) unambiguously. Furthermore, we also consider the case of multiple monofrequency sources that can be separated in the frequency domain, and especially, the effect of sources' frequency spacing on initial phase calibration is analyzed. Finally, the performance of the proposed algorithm under different rotation angles is demonstrated, and its superiority over the rotary 3-D multiple signal classification estimator in computational complexity is also presented.

Localization of Near-Field Sources Based on Sparse Signal Reconstruction with Regularization Parameter Selection

Source localization using sensor array in the near-field is a two-dimensional nonlinear parameter estimation problem which requires jointly estimating the two parameters: direction-of-arrival and range. In this paper, a new source localization method based on sparse signal reconstruction is proposed in the near-field. We first utilize l1-regularized weighted least-squares to find the bearings of sources. Here, the weight is designed by making use of the probability distribution of spatial correlations among symmetric sensors of the array. Meanwhile, a theoretical guidance for choosing a proper regularization parameter is also presented. Then one well-known l1-norm optimization solver is employed to estimate the ranges. The proposed method has a lower variance and higher resolution compared with other methods. Simulation results are given to demonstrate the superior performance of the proposed method.

基于光源近场模型的LED光学扩展量测量方法

基于光源近场模型的LED光学扩展量测量方法

Under-expanded jets and dispersion in high pressure CO2 releases from an industrial scale pipeline

The widespread implementation of carbon capture and storage (CCS) in industry will require extensive long-distance CO2 pipeline networks to integrate the component technologies. The potential for pipeline rupture and leakage, possibly resulting in catastrophic accidents, will inevitably increase as networks become more extensive. The study of near-field source terms and dispersion behavior after pipeline rupture is an essential foundation of CO2 pipeline risk assessment and will provide effective technical support for the implementation of large-scale CCS projects and contribute to pipeline safety. In the CO2QUEST project under-expanded CO2 jets, cloud dispersion characteristics and the formation of dry ice particles in the near field were investigated during releases from a 258 m long, fully instrumented pipeline. Experimental data including cloud temperature, CO2 concentration and the visual evolution of the cloud (recorded on film), was gathered to investigate cloud behavior and to support future work in the field of CO2 pipeline safety. Experiments included the release of gaseous and dense phase CO2 through three orifice diameters: 15 mm, 50 mm and Full Bore Rupture (FBR). The lower limit of gaseous CO2 concentration for adverse effects in humans is 5% v/v. Safety distances from the release, based on this threshold concentration limit, are determined and reported for each experiment conducted.

Extraction of Acoustic Sources Through the Processing of Sound Field Maps in the Ray Space

Our goal is to develop a model-based approach to acoustic source extraction from microphone array data, which is suitable for both near-field and far-field sources. A signal representation based on plane-wave (PW) decomposition is suitable for acoustic sources in the far field as the resulting spectrum turns out to be impulsive. When the source approaches the array, however, the curvature of the wavefront causes the spectrum of the PW components to depart from impulsive behavior, thus making source extraction harder to attain. In this paper, we adopt a sound field representation based on the local estimation of the plenacoustic function along the array line. This approach consists of dividing the array into subarrays, and applying the PW analysis on individual subarrays. This has the immediate result of extending the range of validity of the far-field hypothesis, as a source that enters the near-field range of the extended array is still in the far-field range of the subarrays. PW analysis on subarrays allows us to construct the so-called sound field map in a domain of acoustic visibility called ray space. The extraction of the desired source is accomplished through spatial filtering of the sound field map. The design of the spatial filter relies on a linear minimum mean square error criterion defined on the sound field map. The effectiveness of the proposed methodology is proven through an extensive simulation campaign as well as real experiments.

Compressed Symmetric Nested Arrays and Their Application for Direction-of-Arrival Estimation of Near-Field Sources.

In this paper, a new sensor array geometry, called a compressed symmetric nested array (CSNA), is designed to increase the degrees of freedom in the near field. As its name suggests, a CSNA is constructed by getting rid of some elements from two identical nested arrays. The closed form expressions are also presented for the sensor locations and the largest degrees of freedom obtainable as a function of the total number of sensors. Furthermore, a novel DOA estimation method is proposed by utilizing the CSNA in the near field. By employing this new array geometry, our method can identify more sources than sensors. Compared with other existing methods, the proposed method achieves higher resolution because of increased array aperture. Simulation results are demonstrated to verify the effectiveness of the proposed method.

Conceptual Framework To Extend Life Cycle Assessment Using Near-Field Human Exposure Modeling and High-Throughput Tools for Chemicals.

Life Cycle Assessment (LCA) is a decision-making tool that accounts for multiple impacts across the life cycle of a product or service. This paper presents a conceptual framework to integrate human health impact assessment with risk screening approaches to extend LCA to include near-field chemical sources (e.g., those originating from consumer products and building materials) that have traditionally been excluded from LCA. A new generation of rapid human exposure modeling and high-throughput toxicity testing is transforming chemical risk prioritization and provides an opportunity for integration of screening-level risk assessment (RA) with LCA. The combined LCA and RA approach considers environmental impacts of products alongside risks to human health, which is consistent with regulatory frameworks addressing RA within a sustainability mindset. A case study is presented to juxtapose LCA and risk screening approaches for a chemical used in a consumer product. The case study demonstrates how these new risk screening tools can be used to inform toxicity impact estimates in LCA and highlights needs for future research. The framework provides a basis for developing tools and methods to support decision making on the use of chemicals in products.

Under-expanded jets and dispersion in supercritical CO2 releases from a large-scale pipeline

Long-distance CO2 pipelines will be widely applied to transport captured CO2 from fossil fuel fired power plants for subsequent sequestration. In the event of pipeline failure a large mass of the inventory may be discharged within a short time, this represents a significant hazard if leaks continue undetected. An important result of the risk assessment for a CO2 pipeline is the safety distance. At present the lack of knowledge concerning near-field source terms and the far-field dispersion behavior of CO2 leaking from pipelines can make the calculation of safety distances imprecise. Study of near-field source terms and dispersion behavior is therefore necessary and of paramount importance for assessing safety distances and the impact of CO2 pipeline releases on the surrounding environment. In order to study CO2 pipeline leakage, a large-scale pipeline set-up with a total length of 258m and an internal diameter of 233mm was constructed to study the near-field characteristics and dispersion behavior of supercritical CO2 during sudden releases. The dynamic pressure near the orifice and CO2 concentrations and temperatures within the downstream dispersion region were measured together with the pressures inside the pipeline. The under-expanded jet flow structure and phase transitions in the near-field were studied for supercritical CO2 released though different orifice diameters (15mm, 50mm and Full Bore Rupture). The formation of the visible cloud, the distribution of cloud temperatures and CO2 concentrations in the far-field were analyzed using the measured data, photographs and video recordings. The safety distances along the horizontal direction for 5% CO2 concentration for each of the three orifice diameters were determined from the lower limit for adverse human effects.