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At least 793 records · Page 44

Integrated Logistics Support Analysis of the International Space Station Alpha: An Overview of the Maintenance Time Dependent Parameter Prediction Methods Enhancement

The objective of this publication is to introduce the enhancement methods for the overall reliability and maintainability methods of assessment on the International Space Station. It is essential that the process to predict the values of the maintenance time dependent variable parameters such as mean time between failure (MTBF) over time do not in themselves generate uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. Furthermore, the very acute problems of micrometeorite, Cosmic rays, flares, atomic oxygen, ionization effects, orbital plumes and all the other factors that differentiate maintainable space operations from non-maintainable space operations and/or ground operations must be accounted for. Therefore, these parameters need be subjected to a special and complex process. Since reliability and maintainability strongly depend on the operating conditions that are encountered during the entire life of the International Space Station, it is important that such conditions are accurately identified at the beginning of the logistics support requirements process. Environmental conditions which exert a strong influence on International Space Station will be discussed in this report. Concurrent (combined) space environments may be more detrimental to the reliability and maintainability of the International Space Station than the effects of a single environment. In characterizing the logistics support requirements process, the developed design/test criteria must consider both the single and/or combined environments in anticipation of providing hardware capability to withstand the hazards of the International Space Station profile. The effects of the combined environments (typical) in a matrix relationship on the International Space Station will be shown. The combinations of the environments where the total effect is more damaging than the cumulative effects of the environments acting singly, may include a combination such as temperature, humidity, altitude, shock, and vibration while an item is being transported. The item's acceptance to its end-of-life sequence must be examined for these effects.

Sepehry-Fard, F.↗

Experimental observations and finite element analysis of the initiation of fiber microbuckling in notched composite laminates

A better understanding of the factors that affect the semi-circular edge-notched compressive strength is developed, and the associated failure mode(s) of thermoplastic composite laminates with multidirectional stacking sequences are identified. The primary variables in this investigation are the resin nonlinear shear constitutive behavior, stacking sequence (orientation of plies adjacent to the 0 degree plies), resin-rich regions between the 0 degree plies and the off-axis supporting plies, fiber/matrix interfacial bond strength, and initial fiber waviness. Two thermoplastic composite material systems are used in this investigation. The materials are the commercial APC-2 (AS4/PEEK) and a poor interface experimental material, AU4U/PEEK, designed for this investigation. Notched compression specimens are studied at 21, 77, and 132 C. Geometric and material nonlinear two-dimensional finite element analysis is used to model the initiation of fiber microbuckling of both the ideal straight fiber and the more realistic initially wavy fiber. The effects of free surface, fiber constitutive properties, matrix constitutive behavior, initial fiber curvature, and fiber/matrix interfacial bond strength on fiber microbuckling initiation strain levels are considered.

Guynn, E. Gail↗

Opaque Minerals in the Matrix of the Bishunpur (LL3.1) Chondrite: Constraints on the Chondrule Formation Environment

The chemistry and mineralogy of a group of opaque mineral assemblages in the matrix of the Bishunpur LL3.1 ordinary chondrite provide insight into the nebular environment in which they formed. The assemblages consist of a kamacite (Fe,Ni) core that is rimmed by troilite (FeS) and fayalite (Fe2Si04). Accessory phases in the rims include silica (Si02), chromite (FeCr204), whitlockite (Ca3(P04)2), maricite (FeNaP04), magnetite (Fe304), and tetrataenite (FeNi). We suggest that the metal melted in and equilibrated with an igneous chondrule under high- temperature, reducing conditions. In this environment the molten alloys incorporated varied amounts of Si, Ni, P, Cr, and Co, depending on the oxygen fugacity and temperature of the melt. Some of the metal was subsequently expelled from the chondrule interiors into the surrounding nebular gas. As the temperature dropped, the alloy solidified and volatile elements corroded the metal. The main reaction products were troilite and fayalite. Thermodynamic equilibrium calculations are used to constrain the conditions under which these two phases can form simultaneously in the solar nebula. Kinetic factors are used to place a lower limit on the formation temperature. We determine that the metal corroded between 1173 and 1261 K at a total pressure in the range of 1025.0 to 1024.1 bars and a dust/gas ratio of 302 to 355 x relative to solar composition. These conditions are consistent with our model that the metal corroded in a dust- rich region of the solar nebula that was cooling after a chondrule formation event.

Lauretta, D. S.↗

Molecular Dynamics Modeling of Carbon Nanotube Composite Fracture Using ReaxFF

Carbon nanotube (CNT) fiber reinforced composites with specific tensile strengths and moduli approaching those of aerospace grade carbon fiber composites have recently been reported. This achievement was enabled by the emerging availability of high N/tex yarns in kilometer-scale quantities. While the production of this yarn is an impressive advance, its strength is still much lower than that of the individual CNTs comprising the yarn. Closing this gap requires understanding load transfer between CNTs at the nanometer dimensional scale. This work uses reactive molecular dynamics simulations to gain an understanding at the nanometer scale of the key factors that determine CNT nanocomposite mechanical performance, and to place more realistic upper bounds on the target properties. While molecular dynamics simulations using conventional force fields can predict elastic properties, the ReaxFF reactive forcefield can also model fracture behavior because of its ability to accurately describe bond breaking and formation during a simulation. The upper and lower bounds of CNT composite properties are investigated by comparing systems composed of CNTs continuously connected across the periodic boundary with systems composed of finite length CNTs. These lengths, effectively infinite for the continuous tubes and an aspect ratio of 13 for the finite length case, result from practical limitations on the number of atoms that can be included in a simulation. Experimentally measured aspect ratios are typically on the order of 100,000, so the calculated results should represent upper and lower limits on experimental mechanical properties. Finally, the effect of various degrees of covalent crosslinking between the CNTs and amorphous carbon matrix is considered to identify the amount of CNT-matrix covalent bonding that maximizes overall composite properties.

Jensen, Benjamin D.↗

Determination of ammonium ion by fluorometry or spectrophotometry after on-line derivatization with o-phthalaldehyde

A fast, sensitive, simple, and highly reproducible method for routine assay of ammonium ion (NH4+) was developed by using HPLC equipment. The method is based on the reaction of NH4+ with o-phthalaldehyde (OPA) in the presence of 2-mercaptoethanol. After an on-line derivatization, the resulting NH4(+)-OPA product was quantified by using fluorometric or spectrophotometric detection. For fluorometric detection, the excitation and emission wavelengths were 410 and 470 nm, respectively. The spectrophotometric detection was made by measuring absorbance at 410 nm. Results on the effects of OPA-reagent composition and pH, reaction temperature, sample matrix, and linearity of the assay are presented. Even though it took about 2 min from the time of sample injection to the appearance of sample peak, sample injections could be overlapped at an interval of about 1 min. Thus, the actual time needed for analysis was about 1 min per assay. The method can be used in a fully automated mode by using an autosampler injector.

NASA Discipline Life Support Systems↗

Role of Probabilistic Micromechanics Modeling in Establishing Design Allowables in Composites

One of the major challenges in designing with any new material, and particularly with advanced composite materials, is the fidelity of material design allowables. In the case of composite materials, the concern arises from the inherent nature of these materials, i.e., their heterogeneous make-up and the various factors that affect their properties in a specific design environment. Composites have various scales - micro, macro, laminate and structural, as well as numerous other fabrication related parameters. Many advanced composites in aerospace applications involve complex two- and three-dimensional fiber architectures and requires high-temperature processing. Since there are uncertainties associated with each of these, the observed behavior of composite materials shows scatter. Evaluating the effect of each of these variables on the observed scatter in composite properties solely by teSting is cost and time prohibitive. One alternative is to evaluate these effects by computational simulation. The authors have developed probabilistic composite micromechanics techniques by combining woven composite micromechanics and Fast Probability Integration (FPI) techniques to address these issues. In this paper these techniques will be described and demonstrated through selected examples. Results in the form of cumulative distribution functions (CDF) of the composite properties of a MI (melt-infiltrated) SiC/SiC (silicon carbide fiber in a silicon carbide matrix) Composite will be presented. A CDF is a relationship defined by the value of the property (the response variable) with respect to the cumulative probability of occurrence. Furthermore, input variables causing scatter are identified and ranked based upon their sensitivity magnitude. Sensitivity information is very valuable in quality control. How these results can be utilized to develop design allowables so that these materials may be used by structural analysts/designers will also be discussed.

Mital, Subodh K.↗

Probabilistic Micromechanics and Macromechanics for Ceramic Matrix Composites

The properties of ceramic matrix composites (CMC's) are known to display a considerable amount of scatter due to variations in fiber/matrix properties, interphase properties, interphase bonding, amount of matrix voids, and many geometry- or fabrication-related parameters, such as ply thickness and ply orientation. This paper summarizes preliminary studies in which formal probabilistic descriptions of the material-behavior- and fabrication-related parameters were incorporated into micromechanics and macromechanics for CMC'S. In this process two existing methodologies, namely CMC micromechanics and macromechanics analysis and a fast probability integration (FPI) technique are synergistically coupled to obtain the probabilistic composite behavior or response. Preliminary results in the form of cumulative probability distributions and information on the probability sensitivities of the response to primitive variables for a unidirectional silicon carbide/reaction-bonded silicon nitride (SiC/RBSN) CMC are presented. The cumulative distribution functions are computed for composite moduli, thermal expansion coefficients, thermal conductivities, and longitudinal tensile strength at room temperature. The variations in the constituent properties that directly affect these composite properties are accounted for via assumed probabilistic distributions. Collectively, the results show that the present technique provides valuable information about the composite properties and sensitivity factors, which is useful to design or test engineers. Furthermore, the present methodology is computationally more efficient than a standard Monte-Carlo simulation technique; and the agreement between the two solutions is excellent, as shown via select examples.

Murthy, Pappu L. N.↗

Proliferation, differentiation and apoptosis in connexin43-null osteoblasts

Osteoblasts are highly coupled by gap junctions formed primarily by connexin43 (Cx43). We have shown that interference with Cx43 expression or function disrupts transcriptional regulation of osteoblast genes, and that deletion of Cx43 in the mouse causes skeletal malformations, delayed mineralization, and osteoblast dysfunction. Here, we studied the mechanisms by which genetic deficiency of Cx43 alters osteoblast development. While cell proliferation rates were similar in osteoblastic cells derived from calvaria of Cx43-null and wild type mice, camptothecin-induced apoptosis was 3-fold higher in mutant compared to wild type osteoblasts. When grown in mineralizing medium, Cx43-null cells were able to produce mineralized matrix but it took one week longer to reach the same mineralization levels as in normal cells. Likewise, expression of alkaline phosphatase activity per cell--a marker of osteoblast differentiation--was maximal only 2 weeks later in Cx43-null relative to wild-type cells. These observations suggest that Cx43 is important for a normal and timely development of the osteoblastic phenotype. Delayed differentiation and increase programmed cell death may explain the skeletal phenotype of Cx43-null mice.

NASA Discipline Cell Biology↗

Acousto-ultrasonics to Assess Material and Structural Properties

This report was created to serve as a manual for applying the Acousto-Ultrasonic NDE method, as practiced at NASA Glenn, to the study of materials and structures for a wide range of applications. Three state of the art acousto-ultrasonic (A-U) analysis parameters, ultrasonic decay (UD) rate, mean time (or skewing factor, "s"), and the centroid of the power spectrum, "f(sub c)," have been studied and applied at GRC for NDE interrogation of various materials and structures of aerospace interest. In addition to this, a unique application of Lamb wave analysis is shown. An appendix gives a brief overview of Lamb Wave analysis. This paper presents the analysis employed to calculate these parameters and the development and reasoning behind their use. It also discusses the planning of A-U measurements for materials and structures to be studied. Types of transducer coupling are discussed including contact and non-contact via laser and air. Experimental planning includes matching transducer frequency range to material and geometry of the specimen to be studied. The effect on results of initially zeroing the DC component of the ultrasonic waveform is compared with not doing so. A wide range of interrogation problems are addressed via the application of these analysis parameters to real specimens is shown for five cases: Case 1: Differences in density in [0] SiC/RBSN ceramic matrix composite. Case 2: Effect of tensile fatigue cycling in [+/-45] SiC/SiC ceramic matrix composite. Case 3: Detecting creep life, and failure, in Udimet 520 Nickel-Based Super Alloy. Case 4: Detecting Surface Layer Formation in T-650-35/PMR-15 Polymer Matrix Composites Panels due to Thermal Aging. Case 5: Detecting Spin Test Degradation in PMC Flywheels. Among these cases a wide range of materials and geometries are studied.

Kautz, Harold E.↗

Computation of Free-Free Transitions in Atomic Physics: Foundations

The amplitude T for "free-free" processes, such as bremsstrahlung or photo- absorption by an electron in the continuum in the presence of an external field, is usually written as the matrix element of the radiation operator taken between two continuum states. However, unlike the case when at least one of the states is bound, as in radiative transitions, electron capture, or the photo-effect, this expression contains an unphysical term, proportional to a delta-function and is not really the physical amplitude Tphys. This continues to be true for both the velocity and length form of the dipole approximation to the amplitude T. We first give an a priori definition of Tphys in terms of the scattering parts of the continuum functions, which has an obvious interpretation in terms of time-ordered diagrams. We then show that when the formal amplitude is modified by a long- distance cutoff, the modified form approaches Tphys as the cutoff is removed. The modified form then serves as a basis for the definition of a physical velocity dipole amplitude and this in turn leads to an equivalent length form of the dipole amplitude. This exercise provides a clear theoretical basis for many extant calculations in which cutoff factors are introduces somewhat ad hoc, as needed.

Bhatia, A. K.↗

Thermal Analysis and Testing of Candidate Materials for PAIDAE Inflatable Aeroshell

The Program to Advance Inflatable-Decelerators for Atmospheric Entry (PAIDAE) is a NASA project tasked with developing and evaluating viable inflatable-decelerator aeroshell geometries and materials. Thermal analysis of material layups supporting an inflatable aeroshell was completed in order to identify expected material response, failure times, and to establish an experimental test matrix to keep barrier layer materials from reaching critical temperature limits during thermal soak. Material layups were then tested in the 8- foot High Temperature Tunnel (8'HTT), where they were subjected to hypersonic aerothermal heating conditions, similar to those expected for a Mars entry. This paper presents a broad overview of the thermal analysis supporting multiple materials, and layup configurations tested in the 8'HTT at flight conditions similar to those that would be experienced during Mars entry trajectories. Direct comparison of TPS samples tested in the 8'HTT verify that the thermal model accurately predicted temperature profiles when there are up to four materials in the test layup. As the number of material layers in each test layup increase (greater than 4), the accuracy of the prediction decreases significantly. The inaccuracy of the model predictions for layups with more than four material layers is believed to be a result of the contact resistance values used throughout the model being inaccurate. In addition, the harsh environment of the 8'HTT, including hot gas penetrating through the material layers, could also be a contributing factor.

DelCorso, Joseph A.↗

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-ofthe-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Hesham ElAbd↗

A Revised Approach to the ULDB Design

The National Aeronautics and Space Administration Balloon Program has experienced problems in the scaling up of the proposed Ultra Long Duration Balloon. Full deployment of the balloon envelope has been the issue for the larger balloons. There are a number of factors that contribute to this phenomenon. Analytical treatments of the deployment issue are currently underway. It has also been acknowledged that the current fabrication approach using foreshortening is costly, labor intensive, and requires significant handling during production thereby increasing the chances of inducing damage to the envelope. Raven Industries has proposed a new design and fabrication approach that should increase the probability of balloon deployment, does not require foreshortening, will reduce the handling, production labor, and reduce the final balloon cost. This paper will present a description of the logic and approach used to develop this innovation. This development consists of a serial set of steps with decision points that build upon the results of the previous steps. The first steps include limited material development and testing. This will be followed by load testing of bi-axial reinforced cylinders to determine the effect of eliminating the foreshortening. This series of tests have the goal of measuring the strain in the material as it is bi-axially loaded in a condition that closely replicated the application in the full-scale balloon. Constant lobe radius pumpkin shaped test structures will be designed and analyzed. This matrix of model tests, in conjunction with the deployment analyses, will help develop a curve that should clearly present the deployment relationship for this kind of design. This will allow the "design space" for this type of balloon to be initially determined. The materials used, analyses, and ground testing results of both cylinders and small pumpkin structures will be presented. Following ground testing, a series of test flights, staged in increments of increasing suspended load and balloon volume, will be conducted. The first small scale test flight has been proposed for early Spring 2004. Results of this test flight of this new design and approach will presented. Two additional domestic test flights from Ft. Sumner, New Mexico, and Palestine, Texas, and one circumglobal test flight from Australia are planned as part of this development. Future plans for both ground testing and test flights will also be presented.

Smith, Michael↗

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗

Measurements of Erosion Wear Volume Loss on Bare and Coated Polymer Matrix Composites

An investigation was conducted to examine the erosion behavior of uncoated and coated polymer matrix composite (PMC) specimens subjected to solid particle impingement using air jets. The PMCs were carbon-Kevlar (DuPont, Wilmington, DE) fiber-epoxy resin composites with a temperature capability up to 393 K (248 F). Tungsten carbide-cobalt (WC-Co) was the primary topcoat constituent. Bondcoats were applied to the PMC substrates to improve coating adhesion; then, erosion testing was performed at the University of Cincinnati. All erosion tests were conducted with Arizona road-dust (ARD), impinging at angles of 20 and 90 on both uncoated and two-layer coated PMCs at a velocity of 229 m/s and at a temperature of 366 K (200 F). ARD contains primarily 10-m aluminum oxide powders. Vertically scanning interference microscopy (noncontact, optical profilometry) was used to evaluate surface characteristics, such as erosion wear volume loss and depth, surface topography, and surface roughness. The results indicate that noncontact, optical interferometry can be used to make an accurate determination of the erosion wear volume loss of PMCs with multilayered structures while preserving the specimens. The two-layered (WC-Co topcoat and metal bondcoat) coatings on PMCs remarkably reduced the erosion volume loss by a factor of approximately 10. The tenfold increase in erosion resistance will contribute to longer PMC component lives, lower air friction, reduced related breakdowns, decreased maintenance costs, and increased PMC reliability. The decrease in the surface roughness of the coated vanes will lead to lower air friction and will subsequently reduce energy consumption. Eventually, the coatings could lead to overall economic savings.

Miyoshi, Kazuhisa↗

Design Curve Generation for 3D SiC Fiber Architecture

The design tool provides design curves that allow a simple and quick way to examine multiple factors that can influence the processing and key properties of the preforms and their final SiC-reinforced ceramic composites without over obligating financial capital for the fabricating of materials. Tool predictions for process and fiber fraction properties have been validated for a HNS 3D preform.The virtualization aspect of the tool will be used to provide a quick generation of solid models with actual fiber paths for finite element evaluation to predict mechanical and thermal properties of proposed composites as well as mechanical displacement behavior due to creep and stress relaxation to study load sharing characteristic between constitutes for better performance.Tool predictions for the fiber controlled properties of the SiCSiC CMC fabricated from the HNS preforms will be valuated and up-graded from the measurements on these CMC

matrix materials↗

Influence of Thermally-Grown Oxide (TGO) Layer on the Driving Forces Associated with Failure in Environmental Barrier Coating (EBC) Systems

Environmental barrier coatings (EBC) is an enabling technology for the successful application of ceramic matrix composites (CMCs) in air-breathing gas turbine engines. Spallation of environmental barrier coating (EBC) induced by thermally grown oxide (TGO) layer is a key EBC failure mode. The TGO layer, resulting from steam oxidation, grows either from a silicon bond coat layer (if present) or from the silicon carbide (SiC) based substrate itself. Critical thickness of the TGO layer for failure is in the range of 20-30 microns but it can vary due to exposure temperature, microstructure etc. Current work at NASA Glenn Research Center, under the Revolutionary Tools and Methods (RTM) project is aimed at addressing associated failure modes in EBC systems and developing robust analysis tools to aid in the design/analysis of these systems. The objective of the current work is to conduct a sensitivity study to examine the influence of uniformly and non-uniformly grown oxide layers with or without damage on the associated driving forces leading to spallation of the EBC when subjected to isothermal loading. Initial results indicate that the presence of damage (vertical cracks caused by in-plane stresses) enhances the stresses that are present due to non-uniformity. However, the presence of non-uniformity itself is still the main factor influencing the magnitude of peel and shear stresses in the TGO layer.

Mital, Subodh K.↗

Semicarbazide-sensitive amine oxidase and extracellular matrix deposition by smooth-muscle cells

We have recently reported in vivo disruption of collagen and elastin architecture within blood vessel walls resulting from the selective inhibition of the enzyme semicarbazide-sensitive amine oxidase (SSAO). This study further investigates the effects of SSAO inhibition on extracellular matrix deposition by smooth-muscle cells (SMCs) cultured from neonatal rat hearts. SMCs were characterized, SSAO activity was measured, and soluble and insoluble collagen and elastin in the extracellular matrix (ECM) were quantified. Cultured neonatal rat heart SMC exhibited a monotypic synthetic phenotype that likely represents a myofibroblast. Detectable levels of SSAO activity present throughout 30-d culture peaked at 7-14 d, coinciding with the production of ECM. The addition of enzyme inhibitors and alternate SSAO substrates (benzylamine) produced varied and, in some cases, marked changes in SSAO activity as well as in the composition of mature and soluble matrix components. Similar to our previous in vivo findings, in vitro SSAO inhibition produced aberrations in collagen and elastin deposition by heart SMC. Because changes in SSAO activity are associated with cardiovascular pathologic states, this enzyme may play a protective or modulating role by regulating ECM production during pathologic insult.

Allylamine/administration & dosage/analogs & deriv↗