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Special analytical column having in series two separate absorption sections charged with beads of porous polymer and a sample of gas detects traces of hydrocarbons. New method requires only 15 minutes for execution.
This paper describes a novel fault detection technique for hybrid DC/DC converter oscillation diagnosis. The technique is based on principles of feedback control loop oscillation and RF signal modulations, and Is realized by using signal spectral analysis. Real-circuit simulation and analytical study reveal critical factors of the oscillation and indicate significant correlations between the spectral analysis method and the gain/phase margin method. A stability diagnosis index (SDI) is developed as a quantitative measure to accurately assign a degree of stability to the DC/DC converter. This technique Is capable of detecting oscillation at an early stage without interfering with DC/DC converter's normal operation and without limitations of probing to the converter.
Aromatic molecules that can be used as sensors are described. The aromatic sensors include a polycyclic aromatic hydrocarbon core with a five-membered imide rings fused to the core and at least two pendant aryl groups. The aromatic sensor molecules can detect target analytes or molecular strain as a result of changes in their fluorescence, in many cases with on-off behavior. Aromatic molecules that fluoresce at various frequencies can be prepared by altering the structure of the aromatic core or the substituents attached to it. The aromatic molecules can be used as sensors for various applications such as, for example, the detection of dangerous chemicals, biomedical diagnosis, and the detection of damage or strain in composite materials. Methods of preparing aromatic sensor molecules are also described.
The analytical model for resource utilization and the variable node time and conditional node model for the enhanced ATAMM model for a real-time data flow architecture are presented in this research. The Algorithm To Architecture Mapping Model, ATAMM, is a Petri net based graph theoretic model developed at Old Dominion University, and is capable of modeling the execution of large-grained algorithms on a real-time data flow architecture. Using the resource utilization model, the resource envelope may be obtained directly from a given graph and, consequently, the maximum number of required resources may be evaluated. The node timing diagram for one iteration period may be obtained using the analytical resource envelope. The variable node time model, which describes the change in resource requirement for the execution of an algorithm under node time variation, is useful to expand the applicability of the ATAMM model to heterogeneous architectures. The model also describes a method of detecting the presence of resource limited mode and its subsequent prevention. Graphs with conditional nodes are shown to be reduced to equivalent graphs with time varying nodes and, subsequently, may be analyzed using the variable node time model to determine resource requirements. Case studies are performed on three graphs for the illustration of applicability of the analytical theories.
We disclose measurement systems and methods for measuring analytes in target regions of samples that also include features overlying the target regions. The systems include: (a) a light source; (b) a detection system; (c) a set of at least first, second, and third light ports which transmit light from the light source to a sample and receive and direct light reflected from the sample to the detection system, generating a first set of data including information corresponding to both an internal target within the sample and features overlying the internal target, and a second set of data including information corresponding to features overlying the internal target; and (d) a processor configured to remove information characteristic of the overlying features from the first set of data using the first and second sets of data to produce corrected information representing the internal target.
We disclose measurement systems and methods for measuring analytes in target regions of samples that also include features overlying the target regions. The systems include: (a) a light source; (b) a detection system; (c) a set of at least first, second, and third light ports which transmit light from the light source to a sample and receive and direct light reflected from the sample to the detection system, generating a first set of data including information corresponding to both an internal target within the sample and features overlying the internal target, and a second set of data including information corresponding to features overlying the internal target; and (d) a processor configured to remove information characteristic of the overlying features from the first set of data using the first and second sets of data to produce corrected information representing the internal target.
Current models of human visual search have extended the traditional serial/parallel search dichotomy. Two successful models for predicting human visual search are the Guided Search model and the Signal Detection Theory model. Although these models are inherently different, it has been difficult to compare them because the Guided Search model is designed to predict response time, while Signal Detection Theory models are designed to predict performance accuracy. Moreover, current implementations of the Guided Search model require the use of Monte-Carlo simulations, a method that makes fitting the model's performance quantitatively to human data more computationally time consuming. We have extended the Guided Search model to predict human accuracy in target-localization search tasks. We have also developed analytic expressions that simplify simulation of the model to the evaluation of a small set of equations using only three free parameters. This new implementation and extension of the Guided Search model will enable direct quantitative comparisons with human performance in target-localization search experiments and with the predictions of Signal Detection Theory and other search accuracy models.
Bulk rock chemistry is an essential dataset in meteoritics and planetary science [1]. A common method used to obtain the bulk chemistry of meteorites is ICP-MS. While the accuracy, precision and low detection limits of this process are advantageous [2], the sample size used for analysis (approx.70 mg) can be a problem in a field where small and finite samples are the norm. Fused bead analysis is another bulk rock analytical technique that has been used in meteoritics [3]. This technique involves forming a glass bead from ~10 mg of sample and measuring its chemistry using a defocused beam on a microprobe. Though the ICP-MS has lower detection limits than the microprobe, the fused bead method destroys a much smaller sample of the meteorite. Fused bead analysis was initially designed for samples with near-eutectic compositions and low viscosities. Melts generated of this type homogenize at relatively low temperatures and produce primary melts near the sample s bulk composition [3]. The application of fused bead analysis to samples with noneutectic melt compositions has not been validated. The purpose of this study is to test if fused bead analysis can accurately determine the bulk rock chemistry of non-eutectic melt composition meteorites. To determine this, we conduct two examinations of the fused bead. First, we compare ICP-MS and fused bead results of the same samples using statistical analysis. Secondly, we inspect the beads for the presence of crystals and chemical heterogeneity. The presence of either of these would indicate incomplete melting and quenching of the bead.
Prior to the deployment of prolonged deep space missions which may carry increased crew health risks, it is essential to determine the effect that missions beyond the Van Allen Belt will have on physiology. Historically the National Aeronautics and Space Administration (NASA), Human Research Program (HRP) has developed, conducted, and delivered research findings and countermeasures that will maintain the health and safety of crews aboard the International Space Station (ISS) in anticipation of future exploration class missions. To support these objectives, research operations on ISS typically include the collection and storage of human physiological samples and their return to Earth for analysis. Transition to Gateway and Artemis lunar exploration will limit the available up mass and biosample return capability resulting in new challenges to monitor crew health during the mission. The Artemis lunar missions provide a perfect opportunity to assess new technology that could support crew biosample return that is compatible with the severe operational constraints of Artemis mission design. Dried biosample chemistry analysis is a potential technology that can enable the collection of samples and tracking of crew health during these exploration class missions. The development and implementation of dried biosample chemistry technology for tracking immune health, viral reactivation and hormone fluctuations provide a simple alternative strategy for sample collection and sample return (light weight non-conditioned stowage option) for the continuation of human research during Artemis missions. Saliva is established as an informative biosample that has both its own unique available analytes as well as others that are also present in blood. Saliva is already routinely collected from ISS astronauts for the detection of stress hormones and latent virus DNA. The ‘Dry Saliva’ book sample collection/storage protocol, already successfully deployed to ISS, represents a perfect method for collecting biosamples from Gateway and Artemis astronauts because it requires a simple, non-invasive sample collection protocol, minimum volume, and uses non-conditioned storage. We are currently conducting an expanded stability study of the dry saliva analyte platform to include additional stress hormones, cytokines, antimicrobial proteins, and latent virus DNA as well as other markers of immunity and inflammation. Validation testing on parabolic flight will establish collection methods for saliva and blood to dry sampling substrates to finalize the collection protocols for flight. For the new expanded analyte stability study, a short-term stability study with time points out to 14 days has been completed with analysis underway to determine whether additional analytes could be recovered, as well as assessing the best storage conditions for the samples collected. In parallel, a long-term stability study is being conducted out to 1 year to improve the stability of some unstable analytes. To this end, the NASA Johnson Space Center’s Immunology/Virology lab is currently finalizing the saliva dry chemistry platform, including assay compatibility and stability studies. This technology is approved to be implemented, as part of the ‘Biomarkers’ study, during Artemis II through Artemis IV lunar missions.
Following the discovery of an archived set of samples from Stanley Miller's early experiments, analyses were undertaken to better understand the diversity of compounds produced from electric discharges acting on reducing gas mixtures. The paper chromatography methods that Miller used in the 1950s were only capable of detecting a few amino acids and were unable to provide substantial quantitative data relative to today's techniques. Current analytical techniques are much more sensitive and selective, and are capable of precisely quantifying a much larger range of amino acids and their enantiomeric abundances. In one study, preserved dried samples produced by Miller using a lesser-known volcanic apparatus which differed from Miller's classic apparatus in that it utilized an aspirator that injected steam into the electric discharge chamber, simulating a volcanic eruption. The volcanic apparatus produced a wider variety of amino acids than the classic configuration. Prebiotic compounds synthesized in these environments may have locally accumulated where they could have undergone further processing. An additional preserved set of samples from an experiment conducted in 1958 were also found in Miller's archived collection. These samples which had been generated using a mixture of CH4, NH3, H2S and CO2 were collected, catalogued, and stored by Miller, but for unknown reasons were never studied. In our analyses a total of 23 amino acids and 4 amines, including 7 organosulfur compounds, were detected in these samples. The major amino acids with chiral centers are racemic within the accuracy of the measurements, indicating that they are not contaminants introduced during sample storage. This experiment marks the first synthesis of sulfur amino acids from spark discharge experiments designed to imitate primordial environments. The relative yield of some amino acids, in particular the isomers of amino butyric acid, are the highest ever found in a spark discharge experiment. The simulated primordial conditions used by Miller in these experiments may serve as a model for early volcanic plume chemistry and provide insight to the possible roles such plumes may have played in abiotic organic synthesis. Additionally, the overall abundances of the synthesized amino acids in the presence of H2S are very similar to the abundances found in some carbonaceous meteorites, suggesting that H2S may have played an important role in prebiotic reactions in early solar system environments. Although experiments using a variety of gases as components of the primordial Earth's atmospheric composition and a spark discharge apparatus configured according to Miller's original or volcanic design can be readily carried out, the unique opportunity to investigate samples prepared by the pioneer in abiotic synthesis using state of the art analytical methods is of considerable historic interest.
Spectroscopic chemical analysis methods and apparatus are disclosed which employ deep ultraviolet (e.g. in the 200 nm to 300 nm spectral range) electron beam pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor light emitting devices, and hollow cathode metal ion lasers to perform non-contact, non-invasive detection of unknown chemical analytes. These deep ultraviolet sources enable dramatic size, weight and power consumption reductions of chemical analysis instruments. Chemical analysis instruments employed in some embodiments include capillary and gel plane electrophoresis, capillary electrochromatography, high performance liquid chromatography, flow cytometry, flow cells for liquids and aerosols, and surface detection instruments. In some embodiments, Raman spectroscopic detection methods and apparatus use ultra-narrow-band angle tuning filters, acousto-optic tuning filters, and temperature tuned filters to enable ultra-miniature analyzers for chemical identification. In some embodiments Raman analysis is conducted simultaneously with native fluorescence spectroscopy to provide high levels of sensitivity and specificity in the same instrument.
Spectroscopic chemical analysis methods and apparatus are disclosed which employ deep ultraviolet (e.g. in the 200 nm to 300 nm spectral range) electron beam pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor light emitting devices, and hollow cathode metal ion lasers to perform non-contact, non-invasive detection of unknown chemical analytes. These deep ultraviolet sources enable dramatic size, weight and power consumption reductions of chemical analysis instruments. Chemical analysis instruments employed in some embodiments include capillary and gel plane electrophoresis, capillary electrochromatography, high performance liquid chromatography, flow cytometry, flow cells for liquids and aerosols, and surface detection instruments. In some embodiments, Raman spectroscopic detection methods and apparatus use ultra-narrow-band angle tuning filters, acousto-optic tuning filters, and temperature tuned filters to enable ultra-miniature analyzers for chemical identification. In some embodiments Raman analysis is conducted simultaneously with native fluorescence spectroscopy to provide high levels of sensitivity and specificity in the same instrument.
Spectroscopic chemical analysis methods and apparatus are disclosed which employ deep ultraviolet (e.g. in the 200 nm to 300 nm spectral range) electron beam pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor light emitting devices, and hollow cathode metal ion lasers to perform non-contact, non-invasive detection of unknown chemical analytes. These deep ultraviolet sources enable dramatic size, weight and power consumption reductions of chemical analysis instruments. Chemical analysis instruments employed in some embodiments include capillary and gel plane electrophoresis, capillary electrochromatography, high performance liquid chromatography, flow cytometry, flow cells for liquids and aerosols, and surface detection instruments. In some embodiments, Raman spectroscopic detection methods and apparatus use ultra-narrow-band angle tuning filters, acousto-optic tuning filters, and temperature tuned filters to enable ultra-miniature analyzers for chemical identification. In some embodiments Raman analysis is conducted along with photoluminescence spectroscopy (i.e. fluorescence and/or phosphorescence spectroscopy) to provide high levels of sensitivity and specificity in the same instrument.
Quantitative evidence of gas flows in the far upstream region of small nozzles with large boundary layer flow are discussed. Gas mass fluxes were measured using quartz crystal microbalances. Both nitrogen and carbon dioxide gases were used as test gases. Gas deposition rates on the order of 100 monolayers per minute were detected 13 inches upstream of the nozzle exit plane. It is significant to note that the crystals detected gases considerably beyond the Prandtl-Meyer turning angle. The data from these tests will be essential in the formulation of scaling laws and analytical prediction methods for viscous plume behavior.
Pose and orientation of an object is one of the central issues in 3-D recognition problems. Most of today's available techniques require considerable pre-processing such as detecting edges or joints, fitting curves or surfaces to segment images, and trying to extract higher order features from the input images. We present a method based on analytical geometry, whereby all the rotation parameters of any quadric surface are determined and subsequently eliminated. This procedure is iterative in nature and was found to converge to the desired results in as few as three iterations. The approach enables us to position the quadric surface in a desired coordinate system, and then to utilize the presented shape information to explicitly represent and recognize the 3-D surface. Experiments were conducted with simulated data for objects such as hyperboloid of one and two sheets, elliptic and hyperbolic paraboloid, elliptic and hyperbolic cylinders, ellipsoids, and quadric cones. Real data of quadric cones and cylinders were also utilized. Both of these sets yielded excellent results.
Attention is given to fracture mechanics, an analytical method used extensively in the National Space Transportation System to conservatively predict the remaining service life of an article when a flaw or a material defect is detected. These analyses are performed on hardware containing material defects that have been detected by various nondestructive inspection techniques. An expert system being developed to streamline the process so that hardware dispositions may be obtained in a timely and consistent manner is discussed. The expert system reduces the potential for errors due to the manual transcription between the various software programs involved in completing a fracture mechanics analysis. NEXPERT Object, the expert system development shell selected for this purpose, allows the various software programs used in fracture mechanics analyses to be accessed and manipulated from the same platform.
A non-invasive method for determining blood level of an analyte of interest, such as glucose, comprises: generating an excitation laser beam (e.g., at a wavelength of 700 to 900 nanometers); focusing the excitation laser beam into the anterior chamber of an eye of the subject so that aqueous humor in the anterior chamber is illuminated; detecting (preferably confocally detecting) a Raman spectrum from the illuminated aqueous humor; and then determining the blood glucose level (or the level of another analyte of interest) for the subject from the Raman spectrum. Preferably, the detecting step is followed by the step of subtracting a confounding fluorescence spectrum from the Raman spectrum to produce a difference spectrum; and determining the blood level of the analyte of interest for the subject from that difference spectrum, preferably using linear or nonlinear multivariate analysis such as partial least squares analysis. Apparatus for carrying out the foregoing method is also disclosed.
The objective was to evaluate NASCRAC (trademark) version 2.0, a second generation fracture analysis code, for verification and validity. NASCRAC was evaluated using a combination of comparisons to the literature, closed-form solutions, numerical analyses, and tests. Several limitations and minor errors were detected. Additionally, a number of major flaws were discovered. These major flaws were generally due to application of a specific method or theory, not due to programming logic. Results are presented for the following program capabilities: K versus a, J versus a, crack opening area, life calculation due to fatigue crack growth, tolerable crack size, proof test logic, tearing instability, creep crack growth, crack transitioning, crack retardation due to overloads, and elastic-plastic stress redistribution. It is concluded that the code is an acceptable fracture tool for K solutions of simplified geometries, for a limited number of J and crack opening area solutions, and for fatigue crack propagation with the Paris equation and constant amplitude loads when the Paris equation is applicable.