Analysis of a new negevirus-like sequence from Bemisia tabaci unveils a potential new taxon linking nelorpi- and centiviruses.

This study presents the complete genome sequence of a novel nege-like virus identified in whiteflies (Bemisia tabaci MEAM1), provisionally designated as whitefly negevirus 1 (WfNgV1). The virus possesses a single-stranded RNA genome comprising 11,848 nucleotides, organized into four open reading frames (ORFs). These ORFs encode the putative RNA-dependent-RNA-polymerase (RdRp, ORF 1), a glycoprotein (ORF 2), a structural protein with homology to those in the SP24 family, (ORF 3), and a protein of unknown function (ORF 4). Phylogenetic analysis focusing on RdRp and SP24 amino acid sequences revealed a close relationship between WfNgV1 and Bemisia tabaci negevirus 1, a negevirus sequence recently discovered in whiteflies from Israel. Both viruses form a clade sharing a most recent common ancestor with the proposed nelorpivirus and centivirus taxa. The putative glycoprotein from ORF 2 and SP24 (ORF 3) of WfNgV1 exhibit the characteristic topologies previously reported for negevirus counterparts. This marks the first reported negevirus-like sequence from whiteflies in the Americas.

Invertibility of the dual energy x-ray data transform.

PURPOSE: The Alvarez-Macovski method extracts the x-ray energy-dependent information by expanding the attenuation coefficient as a linear combination of functions of energy multiplied by basis set coefficients. Since the basis functions are known a priori, the coefficients represent all the energy-dependent information. The method then computes the line integrals of these coefficients, summarized as a vector A, from measurements with multiple x-ray spectra, summarized as a vector L. The purpose of this paper is to determine the factors that affect the invertibility of the L(A) transformation with a two function basis set and two spectral measurements, the dual energy transformation. METHODS: A general invertibility theorem is applied that requires testing for zero values of the Jacobian of the transformation in its input domain. General conditions for invertibility are proved. It is shown that the generalized A vector noise variance is proportional to the generalized measurement noise variance divided by the square of the Jacobian. The relationship between the zero Jacobian values and ambiguous sets of A vector points with the same L values is determined. The effect of zero Jacobian values on an iterative algorithm that inverts L(A) is simulated. RESULTS: The choice of a particular valid basis set does not affect invertibility. Nonoverlapping measurement spectra such as those from photon counting detectors with perfect pulse height analysis are invertible. The widely used x-ray tube spectra with different voltages are shown to be invertible. Spectra with the same maximum energy, such as those from layered detectors, approach noninvertibility with small absolute value Jacobian for large object thicknesses. The zero Jacobian values fall on curves in A vector space that, except for a simple artificial case, are close to but not exactly straight lines. With noninvertible spectra, pairs of ambiguous points are located on opposite sides of the zero Jacobian curve. The iterative algorithm has large convergence errors near zero Jacobian curves and converges to the closest ambiguous point to the initial estimate for other points. CONCLUSION: The invertibility of dual energy systems is determined by the presence of zero values of the Jacobian of the dual x-ray energy data transformation L(A) in the input domain.

Forensic microanalysis of Manhattan Project legacy radioactive wastes in St. Louis, MO.

Radioactive particulate matter (RPM) in St Louis, MO, area surface soils, house dusts and sediments was examined by scanning electron microscopy with energy dispersive X-ray analysis. Analyses found RPM containing 238U and decay products (up to 46 wt%), and a distinct second form of RPM containing 230Th and decay products (up to 15.6 wt%). The SEM-EDS analyses found similar RPM in Manhattan Project-era radioactive wastes and indoor dusts in surrounding homes.

Efficient, Non-Iterative Estimator for Imaging Contrast Agents With Spectral X-Ray Detectors.

An estimator to image contrast agents and body materials with x-ray spectral measurements is described. The estimator is usable with the three or more basis functions that are required to represent the attenuation coefficient of high atomic number materials. The estimator variance is equal to the Cramèr-Rao lower bound (CRLB) and it is unbiased. Its parameters are computed from measurements of a calibration phantom with the clinical x-ray system and it is non-iterative. The estimator is compared with an iterative maximum likelihood estimator. The estimator first computes a linearized maximum likelihood estimate of the line integrals of the basis set coefficients. Corrections for errors in the initial estimates are computed by interpolation with calibration phantom data. The final estimate is the initial estimate plus the correction. The performance of the estimator is measured using a Monte Carlo simulation. Random photon counting with pulse height analysis data are generated. The mean squared errors of the estimates are compared to the CRLB. The random data are also processed with an iterative maximum likelihood estimator. Previous implementations of iterative estimators required advanced physics instruments not usually available in clinical institutions. The estimator mean squared error is essentially equal to the CRLB. The estimator outputs are close to those of the iterative estimator but the computation time is approximately 180 times shorter. The estimator is efficient and has advantages over alternate approaches such as iterative estimators.

Tracking legacy radionuclides in St. Louis, Missouri, via unsupported (210)Pb.

Analysis of 287 soil, sediment and house dust samples collected in a 200 km(2)-zone in northern St. Louis County, Missouri, establish that offsite migration of radiological contaminants from Manhattan Project-era uranium processing wastes has occurred in this populated area. Specifically, 48% of samples (111 of a subset of 229 soils and sediments tested) had (210)Pb concentrations above the risk-based soil cleanup limits for residential farming established by the US Department of Energy at the Fernald, OH, uranium plant, which handled and stored the same concentrated Manhattan Project-era wastes; the geographical distribution of the exceedances are consistent with water and radon gas releases from a landfill and related sites used to store and dispose of legacy uranium wastes; and offsite soil and house dust samples proximal to the landfill showed distinctive secular disequilibrium among uranium and its progeny indicative of uranium ore processing wastes. The secular disequilibrium of uranium progeny in the environment provides an important method for distinguishing natural uranium from industrial uranium wastes. In this study, the detection of unsupported (210)Pb beyond expected atmospheric deposition rates is examined as a possible indicator of excessive radon emissions from buried uranium and radium-containing wastes.

Signal to noise ratio of energy selective x-ray photon counting systems with pileup.

PURPOSE: To derive fundamental limits on the effect of pulse pileup and quantum noise in photon counting detectors on the signal to noise ratio (SNR) and noise variance of energy selective x-ray imaging systems. METHODS: An idealized model of the response of counting detectors to pulse pileup is used. The model assumes a nonparalyzable response and delta function pulse shape. The model is used to derive analytical formulas for the noise and energy spectrum of the recorded photons with pulse pileup. These formulas are first verified with a Monte Carlo simulation. They are then used with a method introduced in a previous paper [R. E. Alvarez, "Near optimal energy selective x-ray imaging system performance with simple detectors," Med. Phys. 37, 822-841 (2010)] to compare the signal to noise ratio with pileup to the ideal SNR with perfect energy resolution. Detectors studied include photon counting detectors with pulse height analysis (PHA), detectors that simultaneously measure the number of photons and the integrated energy (NQ detector), and conventional energy integrating and photon counting detectors. The increase in the A-vector variance with dead time is also computed and compared to the Monte Carlo results. A formula for the covariance of the NQ detector is developed. The validity of the constant covariance approximation to the Cramèr-Rao lower bound (CRLB) for larger counts is tested. RESULTS: The SNR becomes smaller than the conventional energy integrating detector (Q) SNR for 0.52, 0.65, and 0.78 expected number photons per dead time for counting (N), two, and four bin PHA detectors, respectively. The NQ detector SNR is always larger than the N and Q SNR but only marginally so for larger dead times. Its noise variance increases by a factor of approximately 3 and 5 for the A1 and A2 components as the dead time parameter increases from 0 to 0.8 photons per dead time. With four bin PHA data, the increase in variance is approximately 2 and 4 times. The constant covariance approximation to the CRLB is valid for larger counts such as those used in medical imaging. CONCLUSIONS: The SNR decreases rapidly as dead time increases. This decrease places stringent limits on allowable dead times with the high count rates required for medical imaging systems. The probability distribution of the idealized data with pileup is shown to be accurately described as a multivariate normal for expected counts greater than those typically utilized in medical imaging systems. The constant covariance approximation to the CRLB is also shown to be valid in this case. A new formula for the covariance of the NQ detector with pileup is derived and validated.

Dimensionality and noise in energy selective x-ray imaging.

PURPOSE: To develop and test a method to quantify the effect of dimensionality on the noise in energy selective x-ray imaging. METHODS: The Cramèr-Rao lower bound (CRLB), a universal lower limit of the covariance of any unbiased estimator, is used to quantify the noise. It is shown that increasing dimensionality always increases, or at best leaves the same, the variance. An analytic formula for the increase in variance in an energy selective x-ray system is derived. The formula is used to gain insight into the dependence of the increase in variance on the properties of the additional basis functions, the measurement noise covariance, and the source spectrum. The formula is also used with computer simulations to quantify the dependence of the additional variance on these factors. Simulated images of an object with three materials are used to demonstrate the trade-off of increased information with dimensionality and noise. The images are computed from energy selective data with a maximum likelihood estimator. RESULTS: The increase in variance depends most importantly on the dimension and on the properties of the additional basis functions. With the attenuation coefficients of cortical bone, soft tissue, and adipose tissue as the basis functions, the increase in variance of the bone component from two to three dimensions is 1.4 × 10(3). With the soft tissue component, it is 2.7 × 10(4). If the attenuation coefficient of a high atomic number contrast agent is used as the third basis function, there is only a slight increase in the variance from two to three basis functions, 1.03 and 7.4 for the bone and soft tissue components, respectively. The changes in spectrum shape with beam hardening also have a substantial effect. They increase the variance by a factor of approximately 200 for the bone component and 220 for the soft tissue component as the soft tissue object thickness increases from 1 to 30 cm. Decreasing the energy resolution of the detectors increases the variance of the bone component markedly with three dimension processing, approximately a factor of 25 as the resolution decreases from 100 to 3 bins. The increase with two dimension processing for adipose tissue is a factor of two and with the contrast agent as the third material for two or three dimensions is also a factor of two for both components. The simulated images show that a maximum likelihood estimator can be used to process energy selective x-ray data to produce images with noise close to the CRLB. CONCLUSIONS: The method presented can be used to compute the effects of the object attenuation coefficients and the x-ray system properties on the relationship of dimensionality and noise in energy selective x-ray imaging systems.

Estimator for photon counting energy selective x-ray imaging with multibin pulse height analysis.

PURPOSE: This paper describes a noniterative estimator for the energy dependent information from photon counting detectors with multibin pulse height analysis (PHA). The estimator uses the two function decomposition of the attenuation coefficient [R. E. Alvarez and A. Macovski, Phys. Med. Biol. 21, 733-744 (1976)] and its output is the line integrals of the basis set coefficients. The output noise variance and bias is compared to other noniterative estimators and to the Cramèr-Rao lower bound (CRLB). METHODS: The estimator first computes an initial estimate from a linearized maximum likelihood estimator. The errors in the initial estimates are determined at a set of points from measurements on a calibration phantom. The errors at these known points are interpolated to create two-dimensional look up tables of corrections to the initial estimates. During image acquisition, the linearized maximum likelihood estimate for each data point is used as an input to the correction look up tables, and the final output is the sum of the estimate and the correction. The performance of the estimator is compared to generalizations of the polynomial and rational polynomial estimators for multibin data. The estimators are compared by the mean square error (MSE) and its components, the bias, and the variance of the output. The variance is also compared to the CRLB. The performance is simulated with two to five bins PHA data. The CRLB at a fixed object thickness is also computed as a function of the number of bins. RESULTS: For two bin data, all the estimators' variances are equal to the CRLB. With three or more bins, only the proposed estimator achieves the CRLB while the others, which were not optimized for noise performance, have much larger output variance. The bias of the proposed estimator is equal to the polynomial estimator for calibration phantoms with 40 or more steps, that is, 1600 combinations of basis materials, but is larger than the rational polynomial bias. In all cases at the photon counts tested, the MSE is essentially equal to the variance, indicating that the bias errors are negligible compared to the variance. CONCLUSIONS: The estimator provides a noniterative method to compute the energy dependent information from multibin PHA data that achieves the CRLB over a wide range of operating conditions and has low output bias. The estimator can be calibrated based on the measurements of a calibration phantom; so, it does not require measurements of the x-ray energy spectrum or the detector response functions.

Fuel consumption and CO2/pollutant emissions of mobile air conditioning at fleet level - new data and model comparison.

Mobile air conditioning (MAC) systems are the second-largest energy consumers in cars after driving itself. While different measurement series are available to illustrate their behavior in hot ambient conditions, little data are available for lower temperatures. There are also no data available on diesel vehicles, despite these being quite common in Europe (up to 70% of the fleet in some countries). In the present study, six representative modern diesel passenger cars were tested. In combination with data from previous measurements on gasoline cars, a new model was developed - EEMAC = Empa Emission model for Mobile Air Conditioning systems - to predict emissions from air conditioning. The measurements obtained show that A/C activity still occurs at temperatures below the desired interior temperature. The EEMAC model was applied to the average meteorological year of a central European region and compared with the US EPA MOBILE6 model. As temperatures in central Europe are often below 20 degrees C (the point below which the two models differ), the overall results differ clearly. The estimated average annual CO(2) output according to EEMAC is six times higher than that of MOBILE6. EEMAC also indicates that around two-thirds of the fuel used for air conditioning could be saved by switching the MAC system off below 18 degrees C.

Near optimal energy selective x-ray imaging system performance with simple detectors.

PURPOSE: This article describes a method to achieve near optimal performance with low energy resolution detectors. Tapiovaara and Wagner [Phys. Med. Biol. 30, 519-529 (1985)] showed that an energy selective x-ray system using a broad spectrum source can produce images with a larger signal to noise ratio (SNR) than conventional systems using energy integrating or photon counting detectors. They showed that there is an upper limit to the SNR and that it can be achieved by measuring full spectrum information and then using an optimal energy dependent weighting. METHODS: A performance measure is derived by applying statistical detection theory to an abstract vector space of the line integrals of the basis set coefficients of the two function approximation to the x-ray attenuation coefficient. The approach produces optimal results that utilize all the available energy dependent data. The method can be used with any energy selective detector and is applied not only to detectors using pulse height analysis (PHA) but also to a detector that simultaneously measures the total photon number and integrated energy, as discussed by Roessl et al. [Med. Phys. 34, 959-966 (2007)]. A generalization of this detector that improves the performance is introduced. A method is described to compute images with the optimal SNR using projections in a "whitened" vector space transformed so the noise is uncorrelated and has unit variance in both coordinates. Material canceled images with optimal SNR can also be computed by projections in this space. RESULTS: The performance measure is validated by showing that it provides the Tapiovaara-Wagner optimal results for a detector with full energy information and also a conventional detector. The performance with different types of detectors is compared to the ideal SNR as a function of x-ray tube voltage and subject thickness. A detector that combines two bin PHA with a simultaneous measurement of integrated photon energy provides near ideal performance across a wide range of operating conditions. CONCLUSIONS: Low energy resolution detectors can be used in energy selective x-ray imaging systems to produce images with near optimal performance.

Pollutant emissions from vehicles with regenerating after-treatment systems in regulatory and real-world driving cycles.

Regenerating exhaust after-treatment systems are increasingly employed in passenger cars in order to comply with regulatory emission standards. These systems include pollutant storage units that occasionally have to be regenerated. The regeneration strategy applied, the resultant emission levels and their share of the emission level during normal operation mode are key issues in determining realistic overall emission factors for these cars. In order to investigate these topics, test series with four cars featuring different types of such after-treatment systems were carried out. The emission performance in legislative and real-world cycles was monitored as well as at constant speeds. The extra emissions determined during regeneration stages are presented together with the methodology applied to calculate their impact on overall emissions. It can be concluded that exhaust after-treatment systems with storage units cause substantial overall extra emissions during regeneration mode and can appreciably affect the emission factors of cars equipped with such systems, depending on the frequency of regenerations. Considering that the fleet appearance of vehicles equipped with such after-treatment systems will increase due to the evolution of statutory pollutant emission levels, extra emissions originating from regenerations of pollutant storage units consequently need to be taken into account for fleet emission inventories. Accurately quantifying these extra emissions is achieved by either conducting sufficient repetitions of emission measurements with an individual car or by considerably increasing the size of the sample of cars with comparable after-treatment systems.

A proliferation of nuclear waste for the Southeast.

The U.S. Department of Energy's (DOE) Global Nuclear Energy Partnership (GNEP) is being promoted as a program to bring about the expansion of worldwide nuclear energy. Here in the U.S. much of this proposed nuclear power expansion is slated to happen in the Southeast, including here in South Carolina. Under the GNEP plan, the United States and its nuclear partners would sell nuclear power plants to developing nations that agree not to pursue technologies that would aid nuclear weapons production, notably reprocessing and uranium enrichment. As part of the deal, the United States would take highly radioactive spent ("used") fuel rods to a reprocessing center in this country. Upon analysis of the proposal, it is clear that DOE lacks a credible plan for the safe management and disposal of radioactive wastes stemming from the GNEP program and that the high costs and possible public health and environmental impacts from the program pose significant risks, especially to this region. Given past failures to address waste problems before they were created, DOE's rush to invest major public funds for deployment of reprocessing should be suspended.

Lung field segmenting in dual-energy subtraction chest X-ray images.

The purpose of this study was to develop and test a method to delineate lung field boundaries in dual-energy chest x-ray images. The segmenting method uses soft-tissue images and spatial frequency-dependent, background-subtracted images. Large-scale chest anatomy features are located and used to select the lung apices, the lateral lung boundaries, and the lung-mediastinum and lung-diaphragm boundaries. Extraneous parts of the contours are removed and they are joined to form complete lung boundaries. The reliability measure uses a statistical shape model to estimate the probability of occurrence of a contour. The method was experimentally tested with 30 human subject images. It has higher accuracy and specificity and a sensitivity parameter equal to the best previously reported method. The reliability measure is able to detect contours with unusual lung outlines or errors in the processing. The method exploits the characteristics of dual-energy subtraction images to improve lung field segmenting performance.

Comparison of dual energy detector system performance.

Dual energy detector systems are combinations of x-ray detectors, x-ray source spectrum switching, and x-ray filter attenuation that provide two measurements of transmitted flux through the object with different effective spectra. We describe technology independent methods to measure and compare the quantum noise and sensitivity to motion artifacts of these systems. The experimental methods use relatively simple phantoms to measure the parameters in the general mathematical expressions for the noise in the subtracted image. The parameters are used to compute an x-ray energy spectrum quality factor and a subtracted image noise per unit patient dose quality factor. Patient motion causes artifacts in switched spectrum systems, particularly with the heart in chest radiography. We describe a method to measure effective interexposure time using subtracted image data of a uniformly moving object. This parameter measures the sensitivity to patient motion artifacts. We use these methods to compare three examples of systems with different dual energy detector technologies: a passive, "sandwich" detector with two computed radiography plates separated by a copper filter, an "active" detector that uses voltage switching with an electro-optical system and computed radiography plates, and a flat-panel, solid state detector with voltage switching.