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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Automatic translation of MPI source into a latency-tolerant, data-driven form

Hiding communication behind useful computation is an important performance programming technique but remains an inscrutable programming exercise even for the expert. We present Bamboo, a code transformation framework that can realize communication overlap in applications written in MPI without the need to intrusively modify the source code. Bamboo reformulates MPI source into the form of a task dependency graph that expresses a partial ordering among tasks, enabling the program to execute in a data-driven fashion under the control of an external runtime system. Experimental results demonstrate that Bamboo significantly reduces communication delays while requiring only modest amounts of programmer annotation for a variety of applications and platforms, including those employing co-processors and accelerators. Moreover, Bamboo's performance meets or exceeds that of labor-intensive hand coding. The translator is more than a means of hiding communication costs automatically; it demonstrates the utility of semantic level optimization against a wellknown library.

Communication-computation↗
DOE OSTI2018

Search for the heaviest atomic nuclei among the products from reactions of mixed-Cf with a Ca 48 beam

In this paper, the search for new decay chains of oganesson isotopes is presented. The experiment utilized the Dubna Gas Filled Recoil Separator and a highly segmented recoil-decay detection system. The signals from all detectors were analyzed in parallel by digital and analog data acquisition systems. For the first time, a target of mixed californium (51% $^{249}\mathrm{Cf}$, 13% $^{250}\mathrm{Cf}$, and 36% $^{251}\mathrm{Cf})$ recovered from decayed $^{252}\mathrm{Cf}$ sources was produced and irradiated with an intense $^{48}\mathrm{Ca}$ beam. The observation of a new decay chain of $^{294}\mathrm{Og}$ is reported. Finally, the prospects for reaching new isotopes $^{295,296}\mathrm{Og}$ are discussed.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2018

A peak position comparison method for high-speed quantitative Laue microdiffraction data processing

Indexing Laue patterns of a synchrotron microdiffraction scan can take as much as ten times longer than collecting the data, impeding efficient structural analysis using this technique. Here in this paper, a novel strategy is developed. By comparing the peak positions of adjacent Laue patterns and checking the intensity sequence, grain and phase boundaries are identified, requiring only a limited number of indexing steps for each individual grain. Using this protocol, the Laue patterns can be indexed on the fly as they are taken. The validation of this method is demonstrated by analyzing the microstructure of a laser 3D printed multi-phase/multi-grain Ni-based superalloy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quantifying Nitrogen Bioextraction by Seaweed Farms – A Real-time Modeling-Monitoring Case Study in Hood Canal, WA

Anthropogenic nitrogen input is the leading cause of increasing marine eutrophication. Cultivating seaweeds at large scales may provide a viable solution for mitigating eutrophication especially when nitrogen extraction is achieved as an added environmental benefit of biofuel and food production. As the first step to promoting and implementing this solution, it is critical to quantify and assess the effectiveness of nitrogen removal by existing seaweed farms. Pacific Northwest National Laboratory and Hood Canal Mariculture Inc. conducted a case study by applying a coupled modeling-monitoring approach to quantify nitrogen bioextraction by a one-hectare commercial sugar kelp farm in Hood Canal, WA. Through this two-year effort, the project team conducted intensive field monitoring of water quality parameters at the farm site and subsequent laboratory analysis. Meanwhile, the team applied a coupled hydrodynamic-macroalgal growth model to simulate kelp growth and nitrogen bioextraction over the two kelp growing seasons. The model results showed an overall good comparison with field monitoring data and showed the effectiveness of nitrogen removal by kelp farms. The established modeling-monitoring approach can also be transferable for supporting broader research activities in macroalgal farming and eutrophication mitigation.

09 BIOMASS FUELS↗
NASA NTRS1994

Computational Approaches to Vestibular Research

The Biocomputation Center at NASA Ames Research Center is dedicated to a union between computational, experimental and theoretical approaches to the study of neuroscience and of life sciences in general. The current emphasis is on computer reconstruction and visualization of vestibular macular architecture in three-dimensions (3-D), and on mathematical modeling and computer simulation of neural activity in the functioning system. Our methods are being used to interpret the influence of spaceflight on mammalian vestibular maculas in a model system, that of the adult Sprague-Dawley rat. More than twenty 3-D reconstructions of type I and type II hair cells and their afferents have been completed by digitization of contours traced from serial sections photographed in a transmission electron microscope. This labor-intensive method has now been replace d by a semiautomated method developed in the Biocomputation Center in which conventional photography is eliminated. All viewing, storage and manipulation of original data is done using Silicon Graphics workstations. Recent improvements to the software include a new mesh generation method for connecting contours. This method will permit the investigator to describe any surface, regardless of complexity, including highly branched structures such as are routinely found in neurons. This same mesh can be used for 3-D, finite volume simulation of synapse activation and voltage spread on neuronal surfaces visualized via the reconstruction process. These simulations help the investigator interpret the relationship between neuroarchitecture and physiology, and are of assistance in determining which experiments will best test theoretical interpretations. Data are also used to develop abstract, 3-D models that dynamically display neuronal activity ongoing in the system. Finally, the same data can be used to visualize the neural tissue in a virtual environment. Our exhibit will depict capabilities of our computational approaches and some of our findings from their application. For example, our research has demonstrated that maculas of adult mammals retain the property of synaptic plasticity. Ribbon synapses increase numerically and undergo changes in type and distribution (p<0.0001) in type II hair cells after exposure to microgravity for as few as nine days. The finding of macular synaptic plasticity is pertinent to the clinic, and may help explain some. balance disorders in humans. The software used in our investigations will be demonstrated for those interested in applying it in their own research.

Ross, Muriel D.↗
NASA NTRS2010

Multivariate Methods for Prediction of Geologic Sample Composition with Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) uses pulses of laser light to ablate a material from the surface of a sample and produce an expanding plasma. The optical emission from the plasma produces a spectrum which can be used to classify target materials and estimate their composition. The ChemCam instrument on the Mars Science Laboratory (MSL) mission will use LIBS to rapidly analyze targets remotely, allowing more resource- and time-intensive in-situ analyses to be reserved for targets of particular interest. ChemCam will also be used to analyze samples that are not reachable by the rover's in-situ instruments. Due to these tactical and scientific roles, it is important that ChemCam-derived sample compositions are as accurate as possible. We have compared the results of partial least squares (PLS), multilayer perceptron (MLP) artificial neural networks (ANNs), and cascade correlation (CC) ANNs to determine which technique yields better estimates of quantitative element abundances in rock and mineral samples. The number of hidden nodes in the MLP ANNs was optimized using a genetic algorithm. The influence of two data preprocessing techniques were also investigated: genetic algorithm feature selection and averaging the spectra for each training sample prior to training the PLS and ANN algorithms. We used a ChemCam-like laboratory stand-off LIBS system to collect spectra of 30 pressed powder geostandards and a diverse suite of 196 geologic slab samples of known bulk composition. We tested the performance of PLS and ANNs on a subset of these samples, choosing to focus on silicate rocks and minerals with a loss on ignition of less than 2 percent. This resulted in a set of 22 pressed powder geostandards and 80 geologic samples. Four of the geostandards were used as a validation set and 18 were used as the training set for the algorithms. We found that PLS typically resulted in the lowest average absolute error in its predictions, but that the optimized MLP ANN and the CC ANN often gave results comparable to PLS. Averaging the spectra for each training sample and/or using feature selection to choose a small subset of wavelengths to use for predictions gave mixed results, with degraded performance in some cases and similar or slightly improved performance in other cases. However, training time was significantly reduced for both PLS and ANN methods by implementing feature selection, making this a potentially appealing method for initial, rapid-turn-around analyses necessary for Chemcam's tactical role on MSL. Choice of training samples has a strong influence on the accuracy of predictions. We are currently investigating the use of clustering algorithms (e.g. k-means, neural gas, etc.) to identify training sets that are spectrally similar to the unknown samples that are being predicted, and therefore result in improved predictions

Morris, Richard↗
NASA NTRS2012

Detecting Organic Compounds Released from Iron Oxidizing Bacteria using Sample Analysis at Mars (SAM) Like Instrument Protocols

Mars is a planet of great interest for Astrobiology since its past environmental conditions are thought to have been favourable for the emergence life. At present, the Red Planet is extremely cold and dry and the surface is exposed to intense UV and ionizing radiation, conditions generally considered to be incompatible with life as we know it on Earth. It was proposed that the shallow subsurface of Mars, where temperatures can be above freezing and liquid water can exist on rock surfaces, could harbor chemolithoautotrophic bacteria such as the iron oxidizing microorganism Pseudomonas sp. HerB. The Mars Science Laboratory (MSL) mission will provide the next opportunity to carry out in situ measurements for organic compounds of possible biological origin on Mars. One instrument onboard MSL, called the Sample Analysis at Mars (SAM) instrument suite, will carry out a broad and sensitive search for organic compounds in surface samples using either high temperature pyrolysis or chemical extraction followed by gas chromatography mass spectrometry. We present gas chromatograph mass spectrometer (GC/MS) data on crushed olivine rock powders that have been inoculated with Pseudomonas sp. HerB at different concentrations ranging from approx 10(exp 2) to 10(exp 7) cells per gram. The inoculated olivine samples were heated under helium carrier gas flow at 500 C and the pyrolysis products concentrated using a SAM-like hydrocarbon trap set at -20 C followed by trap heating and analysis by GC/Ms. In addition, the samples were also extracted using a low temperature "one-pot" chemical extraction technique using N-methyl, N-(tert-butyldimethylsilyl) trifluoroacetamide (MTBSTFA) as the silylating agent prior to GC/MS analysis. We identified several aldehydes, thiols, and alkene nitriles after pyrolysis GC/MS analysis of the bacteria that were not found in the olivine control samples that had not been inoculated with bacteria. The distribution of pyrolysis products extracted from the bacteria was clearly distinct from similar GC/MS analyses of the carbonaceous meteorite Murchison that was dominated by sulfur containing aromatic compounds. A similar comparison, if organic compounds are detected by SAM on Mars, could be useful to help discriminate between meteoritic or biological origins.

Glavin, D. P.↗
DOE OSTI2019

Gamma Imaging and Mapping Advancements

The SRNL developed GrayQb{sup TM} gamma mapping system has been successfully deployed in field situations. Currently, to get the image from the GrayQb{sup TM} the internal Phosphor Storage Plate (PSP) used to capture radiation images must be recovered and scanned by a ScanX Scanner. Upgrades are being implemented which will enable the GrayQB{sup TM} to read the PSP using a camera and red LEDs then transmit results to a remote location. This will greatly reduce personnel interaction, increasing safety as well as eliminating the need for the ScanX. Upgrades have been based off of the MiniMax, a Los Alamos National Laboratory developed PSP reading device constructed with a Nikon DSLR and a red LED flash to obtain the images from the PSP. The electronics in the upgraded GrayQb{sup TM} need to be both functional and environmentally rugged. A PC/104 was chosen for its wider operational temperature range and its physical durability. The Sony α7 ii and the Mightex are the candidate cameras for the upgrades based on test results. PSPs were exposed to gamma radiation sources at SRS's Health Physics Instrumentation Calibration Laboratory (HPICL). PSPs were tested with both Am-241 and Cs-137. Linear intensity increased with dose verifying UV image simulations. Data collected enabled the PSP intensity to be referenced to a total dose. Further work includes design and implementation of a 3D printed housing for the new camera system. The housing will include the camera, light flash, PSP holders, tungsten dual pinhole, PC/104, dosimeter, and a battery or tethering option. Once the housing is finalized further testing at the HPICL facility is planned for early August. During this testing, the final housing design will capture both Am-241 and Cs-137 images.

3D PRINTING↗
DOE OSTI2011

Temperature-Dependent Measurements of an Inverted Metamorphic Multijunction (IMM) Solar Cell: Preprint

The inverted metamorphic multijunction (IMM) solar cell has demonstrated efficiencies as high as 40.8% at 25 degrees C and 326 suns concentration. The actual operating temperature in a commercial module, however, is likely to be as much as 50-70 degrees C hotter, reaching as high as 100 degrees C. In order to be able to evaluate the cell performance under these real-world operating conditions, wehave measured the open-circuit voltage, short-circuit current density and efficiency at temperatures up to 125 degrees C and concentrations up to 1000 suns, as well as the temperature coefficients of these parameters. Spectral response and one-sun current-voltage characteristics were measured by carefully adjusting the incident spectrum to selectively current-limit the different subcells.Concentrator measurements were taken on a pulsed solar simulator to minimize any additional heating due to the high intensity illumination. We compare our measured values to predictions based on detailed models of various triple junction solar cells. By choosing the optimum bandgaps for high temperature operation, the IMM can potentially result in greater energy production and lower temperaturesensitivity under real operating conditions than a Ge-based solar cell.

14 SOLAR ENERGY↗
DOE OSTI2019

The MicroBooNE continuous readout stream for detection of supernova neutrinos

Since the original detection of core-collapse supernova neutrinos in 1987, all large neutrino experiments seek to detect the neutrinos from the next nearby supernova. Among them, liquid argon time projection chambers (LArTPCs) offer a unique sensitivity to the electron neutrino flux of a supernova. However, the low energy of these events (scale of MeVs), and the fact that all large (multi-tonne) LArTPCs operating at the moment are located near the Earth's surface, and are therefore subject to an intense cosmic ray flux, makes triggering on the supernova neutrinos very challenging. Instead, MicroBooNE has pioneered a novel approach for detecting supernova neutrinos based on a continuous readout stream and a delayed trigger generated by other neutrino detectors (the Supernova Early Warning System, or SNEWS). MicroBooNE's data is stored temporarily for a few days, awaiting a SNEWS alert to prompt the permanent recording of the data. In order to cope with the large data rates produced by the continuous readout of the TPC and the PMT systems of MicroBooNE, FPGA-based zero-suppression algorithms have been developed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Physics-Informed Learning for Predictive Multi-Scale Modeling of Water Cycle and Extreme Events

Climate and earth system models have limited skill in predicting water cycle and associated extremes such as intense rain- and wind-producing storms and resulting hazards across all timescales. Water cycle predictions are inherently limited by the predictability of the chaotic system, but large potential for improving predictions remains untapped due to limited use of data-model integration to improve predictive modeling. This white paper proposes a hybrid data-physics paradigm based on physics-informed neural networks (PINNs) to improve the Energy Exascale Earth System Model (E3SM). In particular, we aim to predict and quantify uncertainties of water cycle processes and low probability high impact events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advances in detection for neutron reflectometry with time-resolved imaging detectors

Thermal neutron detection in neutron scattering science is a challenging endeavour due to a limited number of technologies which are sensitive to these weakly interacting particles. While many improvements to conventional detectors are underway at various facilities, there is a great opportunity to make a leap in performance by combining the spatial resolution benefits of imaging and the temporal resolution and background discrimination of event-driven radiation detectors. This idea has been realized by using a neutron sensitive scintillator read out by a single-photon sensitive camera based on a Timepix3 ASIC. We demonstrate how such data-driven imaging sensors can enable unprecedented performance in neutron reflectometry using the ASTERIX instrument at the Los Alamos Neutron Scattering Center. Several samples were measured with both the new and a conventional 3 He detector systems. The results from this work demonstrate that these imaging based systems can satisfy performance parameters for the future QIKR reflectometer to be built at the Second Target Station at Oak Ridge National Laboratory. Further improvements to the detector are already underway which will allow streamlined and expedited experiments. We demonstrate at least a two order of magnitude increase in detection rate at an acceptable dead time and introduce a new way of tuning the detector efficiency using light collecting optics to accommodate highly intense direct beams which cannot be measured with any current detectors without severe attenuation. This will allow measurements of complete reflectometry profiles and using a single sample measurement combined with fewer direct beam calibration measurements on QIKR and potentially other reflectometers.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A non-LTE analysis of high energy density Kr plasmas on Z and NIF

We report that multi-keV X-ray radiation sources have a wide range of applications, from biomedical studies and research on thermonuclear fusion to materials science and astrophysics. The refurbished Z pulsed power machine at the Sandia National Laboratories produces intense multi-keV X-rays from argon Z-pinches, but for a krypton Z-pinch, the yield decreases much faster with atomic number Z A than similar sources on the National Ignition Facility (NIF) laser at the Lawrence Livermore National Laboratory. To investigate whether fundamental energy deposition differences between pulsed power and lasers could account for the yield differences, we consider the Kr plasma on the two machines. The analysis assumes the plasma not in local thermodynamic equilibrium, with a detailed coupling between the hydrodynamics, the radiation field, and the ionization physics. While for the plasma parameters of interest the details of krypton’s M-shell are not crucial, both the L-shell and the K-shell must be modeled in reasonable detail, including the state-specific dielectronic recombination processes that significantly affect Kr’s ionization balance and the resulting X-ray spectrum. We present a detailed description of the atomic model, provide synthetic K- and L-shell spectra, and compare these with the available experimental data from the Z-machine and from NIF to show that the K-shell yield behavior versus Z A is indeed related to the energy input characteristics. In conclusion, this work aims at understanding the probable causes that might explain the differences in the X-ray conversion efficiencies of several radiation sources on Z and

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2002

The Impact of Urbanization on the Precipitation Component of the Water Cycle: A New Perspective

It is estimated that by the year 2025, 60% of the world s population will live in cities (UNFP, 1999). As cities continue to grow, urban sprawl (e.g., the expansion of urban surfaces outward into rural surroundings) creates unique problems related to land use, transportation, agriculture, housing, pollution, and development. Urban expansion also has measurable impacts on environmental processes. Urban areas modify boundary layer processes through the creation of an urban heat island (UHI). The literature indicates that the signature of the urban heat island effect may be resolvable in rainfall patterns over and downwind of metropolitan areas. However, a recent U.S. Weather Research Program panel concluded that more observational and modeling research is needed in this area (Dabberdt et al. 2000). NASA and other agencies initiated programs such as the Atlanta Land-use Analysis: Temperature and Air Quality Project (ATLANTA) (Quattrochi et al. 1998) which aimed to identify and understand how urban heat islands impact the environment. However, a comprehensive assessment of the role of urban-induced rainfall in the global water and energy cycle (GWEC) and cycling of freshwater was not a primary focus of these efforts. NASA's Earth Science Enterprise (ESE) seeks to develop a scientific understanding of the Earth system and its response to natural or human-induced changes to enable improved prediction capability for climate, weather, and natural hazards (NASA, 2000). Within this mission, the ESE has three basic thrusts: science research to increase Earth system knowledge; an applications program to transfer science knowledge to practical use in society; and a technology program to enable new, better, and cheaper capabilities for observing the earth. Within this framework, a research program is underway to further address the co-relationship between land cover use and change (e.g. urban development) and its impact on key components of the GWEC (e.g., precipitation). This presentation discusses the feasibility of using the TRMM or GPM satellite to identify precipitation anomalies likely caused by urbanization (Shepherd et al. 2002). Recent results from analyses of TRMM data around several major U.S. cities (e.g. Dallas, Atlanta, Houston) will be discussed. The presentation also summarizes a NASA-funded research effort to investigate the phenomenon of urban-induced precipitation anomalies using TRMM (future GPM) satellite-based remote sensing, an intensive ground observation/validation effort near Atlanta, and coupled atmosphere-land numerical modeling techniques.

Shephard, J. Marshal↗
DOE OSTI2016

γ-Ray spectroscopy using a binned likelihood approach

The measurement of a reaction cross section from a pulse height spectrum is a ubiquitous problem in experimental nuclear physics. In γ-ray spectroscopy, this is accomplished frequently by measuring the intensity of full-energy primary transition peaks and correcting the intensities for experimental artifacts, such as detection efficiencies and angular correlations. Implicit in this procedure is the assumption that full-energy peaks do not overlap with any secondary peaks, escape peaks, or environmental back- grounds. However, for complex γ-ray cascades, this is often not the case. Furthermore, this technique is difficult to adapt for coincidence spectroscopy, where intensities depend not only on the detection efficiency, but also the detailed decay scheme. We present a method that incorporates the intensities of the entire spectrum (e.g., primary and secondary transition peaks, escape peaks, Compton continua, etc.) into a statistical model, where the transition intensities and branching ratios can be determined using Bayesian statistical inference. This new method provides an elegant solution to the difficulties associated with analyzing coincidence spectra. Finally, we describe it in detail and examine its efficacy in the analysis of 18 O(p,γ) 19 F and 25 Mg(p,γ) 26 Al resonance data. For the 18 O(p,γ) 19 F reaction, the measured branching ratios improve upon the literature values, with a factor of 3 reduction in the uncertainties.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

A Moist Physics Parameterization Based on Deep Learning

Abstract Current moist physics parameterization schemes in general circulation models (GCMs) are the main source of biases in simulated precipitation and atmospheric circulation. Recent advances in machine learning make it possible to explore data‐driven approaches to developing parameterization for moist physics processes such as convection and clouds. This study aims to develop a new moist physics parameterization scheme based on deep learning. We use a residual convolutional neural network (ResNet) for this purpose. It is trained with 1‐year simulation from a superparameterized GCM, SPCAM. An independent year of SPCAM simulation is used for evaluation. In the design of the neural network, referred to as ResCu, the moist static energy conservation during moist processes is considered. In addition, the past history of the atmospheric states, convection, and clouds is also considered. The predicted variables from the neural network are GCM grid‐scale heating and drying rates by convection and clouds, and cloud liquid and ice water contents. Precipitation is derived from predicted moisture tendency. In the independent data test, ResCu can accurately reproduce the SPCAM simulation in both time mean and temporal variance. Comparison with other neural networks demonstrates the superior performance of ResNet architecture. ResCu is further tested in a single‐column model for both continental midlatitude warm season convection and tropical monsoonal convection. In both cases, it simulates the timing and intensity of convective events well. In the prognostic test of tropical convection case, the simulated temperature and moisture biases with ResCu are smaller than those using conventional convection and cloud parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2010

Size saturation in low energy ion beam synthesized nanoparticles in silica glass: 50 keV Ag{sup -} ions implantation, a case study

Fluence-dependent formation of Ag nanoparticles (NPs) in silica glass by 50 keV Ag{sup -} ions implantation has been studied. Samples implanted with fluences of 2x10{sup 16} ions cm{sup -2} and above are found to show an absorption band at around 410 nm, corresponding to the surface plasmon resonance (SPR) of the Ag NPs in silica glass. An increase in SPR peak intensity with increase in fluence has been observed up to a fluence of 7x10{sup 16} ions cm{sup -2} (F7), after which the absorption intensity shows a saturation. Simulations of the optical absorption spectra also indicated an increase in the absorption intensity and hence the size of the NPs with increase in fluence up to F7, beyond which NP size is seen to saturate. The saturation of fluence and the SPR intensity (or NP size) have been explained as coming due to a break up of larger Ag NPs formed near the surface by displacement spikes induced by subsequently incident Ag ions against their regrowth from the movement of Ag atoms toward the surface and their sputtering loss. Further, we have compared our observations with the earlier data on saturation of fluence and size of NPs in cases of Au and Zn, and concluded that the saturation of both fluence and NP size are general phenomena for low energy high fluence metal ion implantation.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evaluation of oxygenation in the surface layers of biological tissues based on diffuse optical spectroscopy with automated calibration of measurements

To assess the oxygen saturation (oxygenation) in the surface layers of biological tissues (at a depth of 4 mm), a compact system based on diffuse optical spectroscopy (DOS) with reflective measurement geometry in the wavelength range of 520 – 590 nm is proposed. The experimental DOS device is based on a broadband LED source of probe radiation and a spectrometer using a fibre-optic radiation delivery system. To calculate the oxygenation, an original method is proposed based on measuring the intensity of scattered light at four different locations of the source and receiver on the surface of the object under study (four-measurement method). The developed method allows for the device hardware parameters (optical contact with the tissue, transient characteristics of the radiation delivery system) and does not require any additional calibration measurements. The results of testing the DOS system using the four-measurement method for monitoring the oxygen saturation of tissues during the artificial occlusion of the blood vessels agree with the published data of other research teams. (paper)

60 APPLIED LIFE SCIENCES↗