Preset Tolerance Research Articles

Degree of Disequilibrium analysis for automatic selection of kinetic constraints in the Rate-Controlled Constrained-Equilibrium method

The Rate-Controlled Constrained-Equilibrium (RCCE) model reduction scheme for chemical kinetics provides acceptable accuracies with a number of differential equations much lower than the number of species in the underlying Detailed Kinetic Model (DKM). To yield good approximations, however, the method requires accurate identification of the rate controlling constraints. So far, a drawback of the RCCE scheme has been the absence of a fully automatable and systematic procedure that is capable of identifying the best constraints for a given range of thermodynamic conditions and a required level of approximation. In this paper, we propose a new methodology for such identification based on a simple algebraic analysis of the results of a preliminary simulation of the underlying DKM, which is focused on the behaviour of the degrees of disequilibrium (DoD) of the individual chemical reactions. The new methodology is based on computing an Approximate Reduced Row Echelon Form of the Actual Degrees of Disequilibrium (ARREFADD) with respect to a preset tolerance level. An alternative variant is to select an Approximate Singular Value Decomposition of the Actual Degrees of Disequilibrium (ASVDADD). Either procedure identifies a low dimensional subspace in the DoD space, from which the actual DoD traces do not depart beyond a fixed distance related to the preset tolerance (ARREFADD methodology) or to the first neglected singular value of the matrix of DoD traces (ASVDADD methodology). The effectiveness and robustness of the method is demonstrated for the case of a very rapid supersonic nozzle expansion of the products of hydrogen and methane oxycombustion and for the case of methane/oxygen ignition. The results are in excellent agreement with DKM predictions. For both variants of the method, we provide a simple Matlab code implementing the proposed constraint selection algorithm.

Mean spectral characteristics of acoustic gravity waves in the thermosphere‐ionosphere determined from Dynasonde data

AbstractWave‐like disturbances have been observed in the ionospheric plasma for several decades using a wide range of remote sensing techniques. In this paper, the use of Dynasonde‐derived ionospheric “tilt” measurements is demonstrated to determine the dominant features of the underlying acoustic gravity wave spectrum and its height variation. The diurnal ionospheric variability introduces data gaps of varying length and distribution at any constant height level. This excludes the use of conventional fast Fourier transform techniques for spectral calculations. To obtain a complete and accurate image of the height variability of the wave activity in the thermosphere‐ionosphere, a method is required that would provide physically comparable results at all altitudes, regardless of the variations in sampling. In addition, the true geophysical variability should be distinguished from overlapping noise. The proposed solution is a combination of the well‐known Lomb‐Scargle and Welch methods, with the dataset of interest being divided into several overlapping subintervals and the mean spectrum calculated using results for those subintervals for which the power spectral density integral equals the time domain variance within a preset tolerance. The choice of the tolerance value is justified by means of numerical simulations using synthetic data similar to the tilt measurements. The proposed method is verified using a 10 day long dataset obtained with the Wallops Island Dynasonde. Results obtained with this method are compared in this paper with those obtained with a basic implementation and with a filtering method based on the amount of available data. A considerable reduction in the number of artifacts is observed with the use of this innovative approach, allowing reliable conclusions to be derived regarding the acoustic gravity wave spectrum and its height variability.

A Two-stage CNC Interpolation Algorithm for Corner Smoothing Trajectories with Geometric Error and Dynamics Constraints

Corners among linear segments are normally smoothed in order to improve the CNC machining efficiency. The interpolation of the corner smoothing trajectories is important to guarantee high geometric accuracy and good dynamics performance. This paper proposes a two-stage interpolation algorithm for corner smoothing trajectories, which includes the off-line pre-processing stage and the on-line interpolation stage. The off-line pre-processing stage calculates the path lengths, and approximates the relation of spline parameters and spline lengths with 7th order polynomial splines within preset tolerance. The on-line interpolation stage generates interpolated drive commands with the trapezoidal acceleration profile, where chord errors and centripetal accelerations at transition corners are also constrained. Simulation and experiment results show that the proposed interpolation algorithm can improve the machining efficiency and satisfy the preset geometric error and dynamics constraints as well.

Operation and performance of a National Monitoring Network for Radioactivity in Food

In the Netherlands, the EU-mandated nationwide monitoring programme and emergency response plan for radioactivity in food is implemented by RIKILT (the Dutch institute for food safety) by means of the National Monitoring Network for Radioactivity in Food (LMRV). The LMRV consists of 48 individual gamma spectrometers (Food Monitoring System, or FMS) that require little maintenance, are hosted at food processing companies and institutes throughout the Netherlands, and are operated by local personnel. From 2010 to 2013, approximately 900 samples of milk and 500 samples of other food categories were analysed on the FMSs annually, and another 1400 in the specialized radionuclide laboratories operated by RIKILT. The anthropogenic radionuclide cesium-137 (137Cs) was detected in 93 out of 11,143 samples (0.8%), mostly in wild mushrooms, game and honey. Two samples of wild boar exceeded the limit of 600 Bq/kg. In case of a nuclear accident the FMSs are used to validate the radioactive deposition calculated by dispersion models by measuring radionuclides in grass samples. No deposition of artificial radionuclides was measured in the Netherlands after the Fukushima nuclear incident. The precision of the FMSs is within the pre-set tolerance limits of 80–120% for 137Cs, cobalt-60 (60Co) and iodine-131 (131I). For potassium-40 (40K) a systematic error of +10% was observed. The recalibration of the FMSs in 2012 resulted in a reduction of almost 40% in the variation of the precision for 131I (compared to 2010 and 2011). This article describes the network and the individual FMSs, the routine measurements of food and special measurements in case of radioactive contamination, and the performance of the network.

New simulation-based approach for the profile control in a process chamber: Fluid, thermal, and plasma profile

Process chamber is the core unit of chemical vapor deposition and etching, and the physical fields in it have fatal effect on process quality. It is significant and difficult for improving the process performance to regulate the fields’ profiles finely. Two design solutions for the profile regulation are proposed: controllable type and resistance type. A novel profile error feedback method is presented, and a simulation-based auto-design framework is established. The profile error feedback method is in a quasi-closed-loop-control mode. It starts from an initial guessed sequence of the design/control variables and predicts a better sequence via feedback of the profile error between the output-targeted profile and the expected one. It never stops until the profile error is narrowed in the preset tolerance. Three kinds of numerical experiments about the regulation of the thermal, fluid, and plasma profile are set to test the effectiveness and feasibility of the profile error feedback method and the two kinds of design schemes.

Modeling for predicting strength of carbon nanostructures

We have developed a computational scheme to predict stiffness and strength of carbon nanostructures under various loading modes. The prediction method is based on combined molecular mechanics and molecular dynamics simulations to approach a global energy minimum at a given loading level with a preset temperature tolerance of 10−6K. We have applied the present method to various carbon nanostructures including carbon nanotubes (CNTs), graphene, CNT with defects, a CNT-graphene junction and pillared graphene nanostructures. For all cases, we have identified the maximum stress and strain at failure of these carbon nanostructures as well as their critical failure modes, and discussed mechanisms that lead to their catastrophic failure.

Calibrated breast density methods for full field digital mammography: a system for serial quality control and inter-system generalization.

The authors are developing a system for calibrated breast density measurements using full field digital mammography (FFDM). Breast tissue equivalent (BTE) phantom images are used to establish baseline (BL) calibration curves at time zero. For a given FFDM unit, the full BL dataset is comprised of approximately 160 phantom images, acquired prior to calibrating prospective patient mammograms. BL curves are monitored serially to ensure they produce accurate calibration and require updating when calibration accuracy degrades beyond an acceptable tolerance, rather than acquiring full BL datasets repeatedly. BL updating is a special case of generalizing calibration datasets across FFDM units, referred to as cross-calibration. Serial monitoring, BL updating, and cross-calibration techniques were developed and evaluated. BL curves were established for three Hologic Selenia FFDM units at time zero. In addition, one set of serial phantom images, comprised of equal proportions of adipose and fibroglandular BTE materials (50/50 compositions) of a fixed height, was acquired biweekly and monitored with the cumulative sum (Cusum) technique. These 50/50 composition images were used to update the BL curves when the calibration accuracy degraded beyond a preset tolerance of ±4 standardized units. A second set of serial images, comprised of a wide-range of BTE compositions, was acquired biweekly to evaluate serial monitoring, BL updating, and cross-calibration techniques. Calibration accuracy can degrade serially and is a function of acquisition technique and phantom height. The authors demonstrated that all heights could be monitored simultaneously while acquiring images of a 50/50 phantom with a fixed height for each acquisition technique biweekly, translating into approximately 16 image acquisitions biweekly per FFDM unit. The same serial images are sufficient for serial monitoring, BL updating, and cross-calibration. Serial calibration accuracy was maintained within ±4 standardized unit variation from the ideal when applying BL updating. BL updating is a special case of cross-calibration; the BL dataset of unit 1 can be converted to the BL dataset for another similar unit (i.e., unit 2) at any given time point using the 16 serial monitoring 50/50 phantom images of unit 2 (or vice versa) acquired near this time point while maintaining the ±4 standardized unit tolerance. A methodology for monitoring and maintaining serial calibration accuracy for breast density measurements was evaluated. Calibration datasets for a given unit can be translated forward in time with minimal phantom imaging effort. Similarly, cross-calibration is a method for generalizing calibration datasets across similar units without additional phantom imaging. This methodology will require further evaluation with mammograms for complete validation.

The segmented non-uniform dielectric module design for uniformity control of plasma profile in a capacitively coupled plasma chamber

Low-temperature plasma technique is one of the critical techniques in IC manufacturing process, such as etching and thin-film deposition, and the uniformity greatly impacts the process quality, so the design for the plasma uniformity control is very important but difficult. It is hard to finely and flexibly regulate the spatial distribution of the plasma in the chamber via controlling the discharge parameters or modifying the structure in zero-dimensional space, and it just can adjust the overall level of the process factors. In the view of this problem, a segmented non-uniform dielectric module design solution is proposed for the regulation of the plasma profile in a CCP chamber. The solution achieves refined and flexible regulation of the plasma profile in the radial direction via configuring the relative permittivity and the width of each segment. In order to solve this design problem, a novel simulation-based auto-design approach is proposed, which can automatically design the positional sequence with multi independent variables to make the output target profile in the parameterized simulation model approximate the one that users preset. This approach employs an idea of quasi-closed-loop control system, and works in an iterative mode. It starts from initial values of the design variable sequences, and predicts better sequences via the feedback of the profile error between the output target profile and the expected one. It never stops until the profile error is narrowed in the preset tolerance.

Eigenmode analysis of advective–diffusive transport by the compact mapping method

The present study concerns an efficient spectral analysis of advective–diffusive transport in periodic flows by the way of a compact version of the diffusive mapping method. Key to the compact approach is the representation of the scalar evolution by only a small subset of the eigenmodes of the mapping matrix, and capturing the relevant features of the transient towards the homogeneous state. This has been demonstrated for purely advective transport in an earlier study by Gorodetskyi et al. (2012). Here this ansatz is extended to advective–diffusive transport and more complex 3D flow fields, motivated primarily by the importance of molecular diffusion in many mixing processes. The study exposed an even greater potential for such transport problems due to the progressive widening of the spectral gaps in the eigenvalue spectrum of the mapping matrix with increasing diffusion. This facilitates substantially larger reductions of the eigenmode basis compared to the purely advective limit for a given approximation tolerance. The compact diffusive mapping method is demonstrated for a representative three-dimensional prototype micro-mixer. This revealed a reliable prediction of (transient) scalar evolutions and mixing patterns with reductions of the eigenmode basis by up to a factor 2000. The accurate estimation of the truncation error from the eigenvalue spectrum enables the systematic determination of the spectral cut-off for a desired degree of approximation. The validity and universality of the presumed correlation between spectral cut-off and truncation error have been established. This has the important practical consequence that the cut-off can a priori be chosen such that the truncation error remains within a preset tolerance. This offers a way to systematically (and reliably) employ the compact mapping method for an in-depth analysis of advective–diffusive transport.

Enhanced pose normalization and matching of non-rigid objects based on support vector machine modelling

The estimation of 3D surface correspondence constitutes a fundamental problem in shape matching and analysis applications. In the presence of non-rigid shape deformations, the ambiguity of surface correspondence increases together with the complexity of registration algorithms.In this paper, we alleviate this problem by means of 3D pose normalization using One-Class Support Vector Machines (OCSVM). In detail, we show how OCSVM are employed in order to increase the consistency of translation and scale normalization under articulations, extrusions or the presence of outliers. To estimate the relative translation and scale of an object, we use the 3D distribution of points that is modelled by employing OCSVM to estimate the decision surface corresponding to the surface points of the object under a preset tolerance to outliers. By discarding the outliers in the estimation of the object's center and size we compute the canonical pose of the core distribution that is less sensitive to intra-class shape variations. The effectiveness of the proposed method is demonstrated through the increased stability of translation and scale normalization and further justified by improving the precision of content-based 3D object retrieval.

SU‐E‐T‐162: Prospective Treatment Plan Modeling To Guide Patient‐Specific Treatment Setups for Hypofractionated Intracranial and Spinal Radiosurgery

Purpose: Residual patient setup shifts such as 1 mm or 1 degree are commonly observed during online treatment setups of hypofractionated radiosurgery (HRS) of spine and intracranial lesions. To effectively guide patient‐specific setups, a prospective treatment planning approach was developed for such treatments. Methods: For a cohort of intracranial and spinal HRS treatments, individualized setup guidelines were prospectively determined via the following approach: (1) systematically shift and rotate 3D patient image data in incremental small steps. (2) For each step such as 0.1 mm or 0.1 degree, dose distributions from original treatment plan were recalculated. (3) Each resulting dose distributions were then iteratively checked against a set of preset dosimetric criteria for compliance. (4) From step 3, maximum tolerable shift levels along the major axes were then determined. Finally, we tested such an approached on a cohort of treatment cases performed at our institutions. Results: For studied treatment sessions (n=63), the mean maximum tolerable shift levels including rotations projected unto the major axes were determined to be 2.0±0.7mm, 2.1±0.9 mm and 1.9±0.8 mm along the lateral, longitudinal, and vertical axis, respectively. Such tolerance levels were significantly (p=0.02) larger than the machine preset tolerance level of 1.0 mm that commonly enforced for all treatment sessions. However, more than 50% of the treatment sessions exhibited sub‐millimeter tolerance level along certain directions to meet critical structure constraints. For example, a 0.6‐mm anterior maximum shift could incur 36% increase in the maximum dose to the brainstem for one patient case. Conclusion: Patient specific online setup guidelines for HRS has been demonstrated to prevent potential deleterious effects from residual shifts while facilitating online setups by providing more room of larger acceptable shifts for a majority of treatment cases.

Certainty of clearing: Creating a credit-checking tool for OTC derivatives

As regulation moves the swaps markets toward mandatory clearing, participants need an efficient real-time solution to confirm buy-side participants have sufficient credit with their clearing members to ensure their trade will clear. There are several ways that this process, known as ‘certainty of clearing’, can take place The author believes that the ideal way to achieve certainty of clearing is to do the credit check on the trade execution platform itself, by using a flexible hybrid combination of ‘ping’ and ‘push’ protocols. The electronic venue receives uploads of credit limits (push) from the clearing member for a given buy-side customer at the beginning of the trading day, and the clearing member is notified (ping) once the client reaches a pre-set tolerance limit (for example, at 75 per cent). The limit stored within the venue then can be adjusted if the clearing member wishes to do so. Since some execution venues, such as Tradeweb, already have relevant infrastructure, connectivity and relationships, they are well positioned to lead in the provision of pre-trade credit-checking technology to the industry.

An Image Compression Algorithm Based on Multilevel B-Spline

Image compression is a common operation in the digital image processing. In order to get high compression rate while prevent blurred edges, an image compression algorithm based on multilevel B-Spline is proposed. Firstly, image plane is seen as the parameter domain of B-Spline and gray values are seen as value of B-Spline. Then, gray values are approximated by B-Spline iterately and at each iteration control points are double dense of the former iteration. The error criterion used is an absolute one and different tolerances are used for edge points and common points, which make edges still clear in the compressed image. Experiments demonstrate that the algorithm presented guarantees that gray value loss at each pixel is less than a preset tolerance while the edge feature of original image is preserved perfectly.

A New Adaptive Fast Cellular Automaton Neighborhood Detection and Rule Identification Algorithm

An important step in the identification of cellular automata (CA) is to detect the correct neighborhood before parameter estimation. Many authors have suggested procedures based on the removal of redundant neighbors from a very large initial neighborhood one by one to find the real model, but this often induces ill conditioning and overfitting. This is true particularly for a large initial neighborhood where there are few significant terms, and this will be demonstrated by an example in this paper. By introducing a new criteria and three new techniques, this paper proposes a new adaptive fast CA orthogonal-least-square (Adaptive-FCA-OLS) algorithm, which cannot only adaptively search for the correct neighborhood without any preset tolerance but can also considerably reduce the computational complexity and memory usage. Several numerical examples demonstrate that the Adaptive-FCA-OLS algorithm has better robustness to noise and to the size of the initial neighborhood than other recently developed neighborhood detection methods in the identification of binary CA.

LOCAL OPTIMIZATION OF THERMAL STORAGE FOR GREENHOUSES: REDUCTION OF ENERGY INPUT AND IMPROVEMENT OF INNER CLIMATE

In temperate regions, such as the Mediterranean basin, there is a diurnal excess of energy nearly every day of the year, which is usually dissipated through natural ventilation. However, since suboptimal nighttime temperatures limit productivity of unheated greenhouses for several months a year, extracting the daytime excess energy and reusing it to heat the greenhouse during the night would increase productivity, or at least reduce energy consumption of greenhouses that are heated. This heat extraction would have the additional advantage of reducing ventilation requirement thereby increasing the scope for carbon dioxide fertilization. To achieve this, the performance of the greenhouse as a solar collector has to be maximized by an efficient heat exchanging and heat buffering system. The aim of this research was to define the optimum combination of heat exchange rate, maximum water flow rate of a heat storage buffer and buffer capacity in a commercial green¬house in the Mediterranean region (Sicily, Italy, 37 °N), the cost function being represented by the dose (duration × intensity) of low temperature events. The green¬house temperature was calculated through a previously validated greenhouse climate simulation model, applied to one-year of real local data. The effect of the buffer on the cost function was first calculated for a range of heat exchange values followed by a cost function evaluation for nodes of a pre-selected grid, each node representing a value-pair for the other two buffer defining parameters. In this paper we analyze the trend of the cost function with respect to each parameter of the buffer and how this is affected by the preset tolerance of low temperatures. Furthermore, we discuss a simple method to find an “optimal” configuration of the buffer. Finally, a combination of 3000 m3 ha-1 buffer capacity, 45 m3 h-1 ha-1 maximum water flow rate and an overall heat transfer coefficient of 5 W m-2 K-1 is selected (heat transfer coefficient is defined per m2 greenhouse floor area).

Development of Frameless SRS using Real-Time 6D Facial Surface Monitoring and Continuous Adaptive Head Motion Correction

Development of Frameless SRS using Real-Time 6D Facial Surface Monitoring and Continuous Adaptive Head Motion Correction

A Machine Vision Method for Automated Alignment of Fundus Imaging Systems

To report a method to track the pupil in three axes simultaneously prior to imaging the fundus. The system is based on parallax optical alignment to detect the center of the pupil. The system consists of two cameras acquiring pupil images from two distinct directions and an operator-supervised algorithm to derive the coordinates of the pupil center and output of commands to drive a three-axes computer-controlled stage. The system was tested in a cohort of 45 individuals 61 ± 15 years of age, 26 with and 19 without glaucoma. The tracking was performed without pharmacologic pupil dilation. The variability of the pupil center determination (assessed by the standard deviation) was ± 0.19 and ± 0.33 mm for the vertical and horizontal directions, respectively. The processing time of the algorithm was 0.75 msec. The tracking converged to within a preset tolerance of ± 0.5 mm in 45 of the 45 eyes. Image acquisition and processing of pupil images can be used to align fundus imaging systems rapidly, accurately, and with minimal operator intervention.

An automated algorithm for sequence confirmation of chemically modified oligonucleotides by tandem mass spectrometry

We have developed a tandem mass spectrometry (MS/MS) data analysis program for confirmation of sequence of chemically modified oligonucleotides. The method is based on the analysis of deconvoluted MS/MS data for fragment ions from three charge states and comparison of these data against a set of computer-generated masses from expected fragmentation patterns. The algorithm compares the experimental masses not only against the fragment set predicted for the expected sequence but also against a wider test set covering all next-neighbor position switches of the original sequence and all pairwise swaps of nucleosides, which in synthesis would result in molecules with masses within a preset mass tolerance. The algorithm is capable of identifying incorrect sequences that would not be distinguished by identity testing with electrospray ionization mass spectrometry. The method has been tested with permutations of the two 21-mer single strands of a chemically modified short interfering RNA containing 2′- O-methyl and phosphorothioate linkages. For both strands, challenge sequences were synthesized and tested with the premise that they were the original sequences. The algorithm correctly reported the locations of next-neighbor position switches and nucleoside swaps. The results confirm the approach as useful for MS/MS-based identity test methods for synthetic oligonucleotides.

An Effective Method for Modeling Non-Moving Stagnant Liquid Columns in Gas Gathering Systems

Abstract Gas gathering system modeling is often complicated by the presence of localized pressure losses that are not easily explained by traditional pressure loss correlations. The tendency is to assume the pressure loss correlation must be tweaked to match measured operating conditions. This often leads to inappropriate manipulation of tuning factors (efficiency factor or roughness). A more appropriate approach is to recheck the validity of the input data and, most importantly, visit the field prepared to gather additional data to resolve the causes of the localized pressure losses. The objectives of this paper are to discuss one of the causes of localized pressure losses —Stagnant Liquid Columns —and to present several cases where localized pressure losses were interpreted to be caused by stagnant liquid accumulations. Introduction The maturation of the gas gathering systems throughout North America has resulted in the majority of systems being operated well below their original design conditions. Consequently, it is common to encounter pressure losses that exceed those predicted by steady-state single-phase and two-phase correlations. The reasons for these pressure losses are varied and most often relate to measurement issues, poor understanding of the pipeline and facility connections and sometimes non-moving liquid accumulations called stagnant liquid columns. Liquid accumulations are a concern because their continuous removal is difficult and they increase backpressure for all upstream wells, which reduces well deliverability and can result in localized pipeline corrosion. One would think that the traditionally used steady-state two-phase pressure loss equations would be capable of predicting the pressure loss that occurs in these liquid accumulations. However, the steady-state flow of fluid must be, by definition, continuous: inlet rate equal to outflow rate. If the liquid enters the conduit and accumulates while the gas continues through, we no longer have steady-state flow and the validity of the correlation no longer holds. It has been the authors' experience that localized pressure losses are often associated with liquid accumulations. Typically, field staff usually know there is a problem and may or may not have already realized that it is due to liquids, but it is usually a surprise for head-office staff because there is little or no liquid production reported. This leads to the question, how do we reliably identify stagnant liquid columns and how should they be modeled? To answer this question, a discussion of recommended modeling procedures is required. Discussion Pressure Loss Categorization The existing steady-state pressure loss correlations generally do a very good job of estimating pressure losses when used appropriately. Consequently, a comparison of simulated line pressures with field measured line pressures should result in a reasonable match within a preset tolerance. Measured line pressures that do not match modelled line pressures must be scrutinized closely to determine the cause of the mismatch, rather than relying primarily on tweaking tuning factors such as pipeline roughness or flow efficiency. For wells or groups of wells where a reasonable match is not initially obtained, it is good practice to begin by attempting to classify the unmatched pressure losses as either a systemic or localized step pressure loss problem before making changes to the model to force a match.

RT‐PSM, a real‐time program for peptide‐spectrum matching with statistical significance

The analysis of complex biological peptide mixtures by tandem mass spectrometry (MS/MS) produces a huge body of collision-induced dissociation (CID) MS/MS spectra. Several methods have been developed for identifying peptide-spectrum matches (PSMs) by assigning MS/MS spectra to peptides in a database. However, most of these methods either do not give the statistical significance of PSMs (e.g., SEQUEST) or employ time-consuming computational methods to estimate the statistical significance (e.g., PeptideProphet). In this paper, we describe a new algorithm, RT-PSM, which can be used to identify PSMs and estimate their accuracy statistically in real time. RT-PSM first computes PSM scores between an MS/MS spectrum and a set of candidate peptides whose masses are within a preset tolerance of the MS/MS precursor ion mass. Then the computed PSM scores of all candidate peptides are employed to fit the expectation value distribution of the scores into a second-degree polynomial function in PSM score. The statistical significance of the best PSM is estimated by extrapolating the fitting polynomial function to the best PSM score. RT-PSM was tested on two pairs of MS/MS spectrum datasets and protein databases to investigate its performance. The MS/MS spectra were acquired using an ion trap mass spectrometer equipped with a nano-electrospray ionization source. The results show that RT-PSM has good sensitivity and specificity. Using a 55,577-entry protein database and running on a standard Pentium-4, 2.8-GHz CPU personal computer, RT-PSM can process peptide spectra on a sequential, one-by-one basis in 0.047 s on average, compared to more than 7 s per spectrum on average for Sequest and X!Tandem, in their current batch-mode processing implementations. RT-PSM is clearly shown to be fast enough for real-time PSM assignment of MS/MS spectra generated every 3 s or so by a 3D ion trap or by a QqTOF instrument.