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Equations derived for input impedance, input power, and ratio of secondary current to primary current of rotary transformer. Used for quick analysis of transformer designs. Circuit model commonly used in textbooks on theory of ac circuits.
The Passive Optical Sample Assembly-1 (POSA-1), part of the Mir Environmental Effects Payload (MEEP), was designed to study the combined effects of contamination, atomic oxygen, ultraviolet radiation, vacuum, thermal cycling, and other constituents of the space environment on spacecraft materials. The MEEP program is a Phase 1 International Space Station Risk Mitigation Experiment. The payload was attached by EVA to the exterior of the Mir docking module during the Space Shuttle mission STS-76. It was removed during STS-86 after exposure to the Mir environment for 18 months. POSA-1 consists of nearly 400 samples of thermal control paints, chemical conversion coatings, mirrors, optics, and other candidate materials for International Space Station Alpha (ISSA). POSA-1 also flew state-of-the-art materials, such as electrically conductive thermal control coatings developed under contract by IITRI and AZ Technology, and passive instruments for monitoring the atomic oxygen and ultraviolet radiation dose to the experiment. Contamination was detected on the POSA-1 experiment. On the side facing space (-Z(sub B) direction using the Mir coordinate system), visible contamination was observed. The contamination was uniform as would occur from a slow photodeposition process. A very definite film was deposited on the optical samples. The deposition appears to have directionality with definite shadowing effects. On the side facing the main Mr core (+ZB direction using the Mir coordinate system), no visible contamination was noted. Pre- and post-flight characterization of candidate spacecraft materials is discussed, particularly the effect of contamination on total hemispherical spectral reflectance (250 - 2500 nm), infrared emittance, the bi-directional reflectance distribution function (BRDF), and vacuum ultraviolet spectral reflectance. Extensive photography under normal and black light was performed. Results of electron spectroscopy for chemical analysis (ESCA) and Fourier Transform Infrared Analysis (FTIR) on selected samples are also discussed.
Analysis of proteins and complexes under native mass spectrometric (MS) and solution conditions was typically performed using time-of-flight (ToF) analyzers, due to their routine high m/z transmission and detection capabilities. However, over recent years, the ability of Orbitrap-based mass spectrometers to transmit and detect a range of high molecular weight species is well documented. Herein, we describe how a 15 Tesla Fourier transform ion cyclotron resonance mass spectrometer (15 T FT-ICR MS) is more than capable of analyzing a wide range of ions in the high m/z scale (>5000), in both positive and negative instrument polarities, ranging from the inorganic cesium iodide salt clusters; a humanized IgG1k monoclonal antibody (mAb; 148.2 kDa); an IgG1-mertansine drug conjugate (148.5 kDa, drug-to-antibody ratio; DAR 2.26); an IgG1-siRNA conjugate (159.1 kDa; ribonucleic acid to antibody ratio; RAR 1); the membrane protein aquaporin-Z (97.2 kDa) liberated from a C8E4 detergent micelle; the empty MSP1D1-nanodisc (142.5 kDa) and the tetradecameric chaperone protein complex GroEL (806.2 kDa; GroEL dimer at 1.6 MDa). We also investigate different regions of the FT-ICR MS that impact ion transmission and desolvation. Finally, we demonstrate how the transmission of these species and resultant spectra are highly consistent with those previously generated on both quadrupole-ToF (Q-ToF) and Orbitrap instrumentation. This article serves as an impactful example of how FT-ICR mass analyzers are competitive to Q-ToFs and Orbitraps for high mass detection at high m/z.
REopt transforms complex energy project decisions into actionable results for building owners, utilities, and industry. Based on decades of NREL decision-support expertise, REopt guides investment in economic, resilient energy technologies. This presentation provides an overview of how REopt can help building owners, utilities, developers, and industry optimize the economic and resilience benefits of distributed energy resources.
Fourier transform infrared spectrometry has been used to study the products of the photooxidation of ammonia in the presence of oxygen at 296 K. The data have been used to derive an upper limit of 6 x 10 exp -21/cu cm molecule s for the reaction of NH2 radicals with O2 to produce NO(x) at 296 K. This upper limit, which is three orders of magnitude lower than previous estimates based on the kinetics of NH2 loss, rules out the importance of this reaction in the atmosphere and suggests that NH2 will be oxidized by O3 or NO2. The effect on the NO(x) and N2O budgets depends critically on the products of the NH2 + O3 reaction. Simulations of the experimental product yields also allow an evaluation of possible product channels for the reaction of NH2 with HO2.
The charge coupled device (CCD) Chirp Z transformation (CZT) spectral analysis techniques were reviewed and results on state-of-the-art CCD CZT technology are presented. The CZT algorithm was examined and the advantages of CCD implementation are discussed. The sliding CZT which is useful in many spectral analysis applications is described, and the performance limitations of the CZT are studied.
Observations of nonlinear coherent plasma phenomena in spacecraft and terrestrial experiments often rely on visual identification of solitary modes because nonlinear coherent modes are broadband in a Fourier transform based analysis. We implement an alternative spectral decomposition known as the inverse scattering transform and demonstrate its ability to successfully isolate nonlinear modes on the homogeneous and forced Korteweg–De Vries equation which models these nonlinear modes. We also demonstrate for the first time that this decomposition is useful when forcing is applied. This is because the stable modes generated by localized forcing are similar to the homogeneous solutions where the inverse scattering transform is a rigorous decomposition. This spectral technique is then applied to simulations of ion acoustic waves generated by a 10 mm spherical debris object interacting with the ionospheric plasma orbiting at 2000 km altitude. The algorithm is found to successfully detect the resultant solitons. This demonstrates the feasibility of using this spectral technique as a real time analysis tool for screening spacecraft data for nonlinear solitary modes.
Relationships between the Euler angles and the transformation matrix, the quaternion and the transformation matrix, and the Euler angles and the quaternion are analyzed, and equations developed are applied directly to current space shuttle problems. The twelve three-axis Euler transformation matrices as functions of the Euler angles, the equations for the quaternion as a function of the Euler angles, and the Euler angles as a function of the transformation matrix elements are included along with a group of utility subroutines to accomplish the Euler matrix, quaternion matrix, and Euler quaternion relationships.
Matrix multiplication algorithm based on degrees of freedom analysis for various transformations and spectral analysis
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Quantum Machine Learning (QML) offers a promising paradigm that leverages quantum computing principles to develop efficient and expressive models for learning from complex and structured data. Recent advances in natural language processing (NLP) and artificial intelligence (AI) have demonstrated capabilities in understanding, generating, and reasoning over linguistic and multimodal information. In this work, we present the Quantum Graph Transformer (QGT), a hybrid quantum–classical architecture that extends graph transformer capabilities through quantum self-attention. The QGT models variable-length sentences as token graphs, where both the embedding encoding and the self-attention mechanisms are implemented using parameterized quantum circuits (PQCs), enabling efficient contextual learning with significantly fewer trainable parameters. We train QGT using both fully connected and 𝑘 -nearest-neighbor graph structures and evaluate it on five benchmark sentiment-classification datasets. Experimental results show that QGT consistently achieves higher or comparable accuracy to existing quantum NLP models and outperforms a Classical Graph Transformer (CGT) baseline with identical architecture, achieving 29.4 × fewer parameters while requiring 3–5 × fewer samples to reach comparable performance. These findings highlight the potential of graph-based quantum models as scalable and data-efficient architectures for natural language understanding.
The pyrolysis of lignocellulosic materials is a promising technique to produce fuels and chemicals. It is well known that the most abundant products of lignin pyrolysis are oligomeric molecules, known as pyrolytic lignin (PL). The chemical composition of PL has been extensively studied; however, there is still an important debate whether these oligomers are produced directly from the lignin or from the recombination of monomeric pyrolytic products. Existing theories are unable to describe the effect of vacuum on the distribution of pyrolysis products. Hybrid poplar milled wood lignin (MWL) was initially isolated and thoroughly characterized by Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR MS). Chemical formulas were assigned to each oligomeric compound detected. The MWL was also subjected to vacuum pyrolysis in a modified pyroprobe at 250, 750, and 1000 mbar (absolute pressure), and the resulting liquid products were analyzed by FT-ICR MS. A new strategy to assign structural representations to the oligomeric PL products is proposed, based on the plausible pyrolysis reaction mechanisms of depolymerization/fragmentation applied to original MWL oligomer formulas. Our results support the hypothesis that PL is formed from the removal of moieties from primary lignin pyrolysis products with between three and five aromatic rings. This depolymerization/fragmentation allows the oligomers to reduce their molecular weights to the point where they can be removed from the reaction zone by direct vaporization. Furthermore, this phenomenon highlights the importance of pressure on removal mechanisms and their impact on the molecular weight of the resulting products from lignin pyrolysis.
A fast Fourier transform technique is given for the simulation of those distortion effects in the instrument line shape of the interferometric spectrum that are due to errors in the measured interferogram. The technique is applied to analyses of atmospheric absorption spectra and laboratory spectra. It is shown that the nonlinear least squares method can retrieve the correct information from the distorted spectrum. Analyses of HF absorption spectra obtained in a laboratory and solar CO absorption spectra gathered by a balloon-borne interferometer indicate that the retrieved amount of absorbing gas is less than the correct value in most cases, if the interferogram distortion effects are not included in the analysis.
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The quantization error introduced by the Winograd Fourier transform algorithm (WFTA) when implemented in fixed-point arithmetic is studied and compared with that of the fast Fourier transform (FFT). The effect of ordering the computational modules and the relative contributions of data quantization error and coefficient quantization error are determined. In addition, the quantization error introduced by the Good-Winograd (GW) algorithm, which uses Good's prime-factor decomposition for the discrete Fourier transform (DFT) together with Winograd's short length DFT algorithms, is studied. Error introduced by the WFTA is, in all cases, worse than that of the FFT. In general, the WFTA requires one or two more bits for data representation to give an error similar to that of the FFT. Error introduced by the GW algorithm is approximately the same as that of the FFT.