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Analytical procedure simplifies prediction of frequency response of multirate digital control systems. Although developed for Space Shuttle flightcontrol system, procedure is applicable to any multirate system describable by linear, constant-coefficient differential equations of difference equations.
Astronauts lose bone structure during long-duration spaceflight. These changes are due, in part, to insufficient bone formation by the osteoblast cells. Little is known about the role that small (approximately 22 nucleotides), non-coding micro-RNAs (miRNAs) play in the osteoblast response to microgravity. We hypothesize that osteoblast-lineage cells alter their miRNA status during microgravity exposure, contributing to impaired bone formation during weightlessness. To simulate weightlessness, female mice (C57BL/6, Charles River, 10 weeks of age, n = 7) were hindlimb unloaded up to 12 days. Age-matched and normally ambulating mice served as controls (n=7). To assess the expression of miRNAs in skeletal tissue, the tibia was collected ex vivo and cleaned of soft-tissue and marrow. Total RNA was collected from tibial bone and relative abundance was measured for miRNAs of interest using quantitative real time PCR array looking at 372 unique and well-characterized mature miRNAs using the delta-delta Ct method. Transcripts of interest were normalized to an average of 6 reference RNAs. Preliminary results show that hindlimb unloading decreased the expression of 14 miRNAs to less than 0.5 times that of the control levels and increased the expression of 5 miRNAs relative to the control mice between 1.2-1.5-fold (p less than 0.05, respectively). Using the miRSystem we assessed overlapping target genes predicted to be regulated by multiple members of the 19 differentially expressed miRNAs as well as in silico predicted targets of our individual miRNAs. Our miRsystem results indicated that a number of our differentially expressed miRNAs were regulators of genes related to the Wnt-Beta Catenin pathway-a known regulator of bone health-and, interestingly, the estrogen-mediated cell-cycle regulation pathway, which may indicate that simulated weightlessness modulated systemic hormonal levels or hormonal transduction that additionally contributed to bone loss. We plan to follow up these findings by measuring gene expression of miRNA-regulated genes within these two pathways with the aim of furthering our understanding of the function of miRNAs in the skeletal response to spaceflight.
Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), has typically limited machine learning (ML) in space studies and further study of radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNAseq) data from 6 mouse liver GeneLab datasets (GLDS) with a total of 113 spaceflight and ground-control samples to determine top features relevant to spaceflight including the effect of radiation exposure. Data was normalized within each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. The top MRMR features were used to predict spaceflight vs. ground-control samples using a Random Forest (RF) classifier with 5-fold cross validation (CV). The ML-based gene sets were further compared against differential gene expression results from individual GLDS. CV training using the top 100 MRMR genes show averages of 86% accuracy and 0.95 AUC value on the validation set over 5 folds (Figure 1A). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 811 or 68 DEGs overlapping between at least 2 or 3 studies, respectively (Figure 1B). Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism. Set analysis between the MRMR features and the DEGs showed 60 or 8 genes overlapping with at least 1 or 2 studies, respectively. MRMR feature selection and ensemble ML methods (e.g. RF) improve performance relative to a Naïve Bayes classifier when NGS data sets are analyzed. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise ratio. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from RNASeq analysis. Non-intersecting sets introduce opportunity to explore spaceflight relevant genes and implementing ML methods across existing NGS datasets may overcome sample size limitations. ML coupled with existing analytical methods enhances understanding of disease by revealing common underlying pathways across datasets.
Computer program developed for solving nonlinear differential equations of motion of high-speed, lightly loaded, cylindrical roller bearing. Program organized into three major parts: Main program, controls input and output; differential equation solver; and subroutines, used to evaluate vector function. Program has capability of performing either twodimensional or three-dimensional simulation.
Four Arde conospheroid metallic diaphragms were tested at NASA to evaluate their capability for use in the orbit adjust propulsion subsystem (OAPS) of the Atmosphere Explorer spacecraft (AE's C, D, and E). The diaphragms will be used for positive propellant expulsion and spacecraft center of mass (c.m.) control. A leak-free cycle life capability of nine reversals was demonstrated. The diaphragms rolled smoothly from ring to ring in a predictable manner on the first reversal. Varying amounts of diaphragm cocking and ring skipping were observed on subsequent reversals. The diaphragm pressure differential did not exceed 10 psid during any reversal. Cycle life capability, reversal mode, and pressure differential were not affected by sudden reversals, environmental tests, or 18,000 partial reversals. An expulsion efficiency of approximately 97 percent was demonstrated. The results of these tests show that metallic diaphragms can be used as an effective means of positive fuel expulsion; however, to achieve spacecraft c.m. control, the diaphragm must not be reversed prior to flight.
Four Arde conospheroid metallic diaphragms were tested to evaluate their capability for use in the orbit adjust propulsion subsystem (OAPS) of the Explorer spacecraft. The diaphragms will be used for positive propellant expulsion and spacecraft center of mass control. A leak-free cycle life capability of nine reversals was demonstrated. The diaphragms rolled smoothly from ring to ring in a predictable manner on the first reversal. Varying amounts of diaphragm cocking and ring skipping were observed on subsequent reversals. The diaphragm pressure differential did not exceed 7 N/sq cm during any reversal. Cycle life capability, reversal mode, and pressure differential were not affected by sudden reversals, environmental tests, or 18,000 partial reversals. An expulsion efficiency of approximately 97 percent was demonstrated. The results of these tests show that metallic diaphragms can be used as an effective means of positive fuel expulsion; however, to achieve spacecraft center of mass control, the diaphragm must not be reversed prior to flight.
Dynamics analysis of RR interval behavior and traditional measures of heart rate variability were compared between postinfarction patients with and without vulnerability to ventricular tachyarrhythmias in a case-control study. Short-term fractal correlation of heart rate dynamics was better than traditional measures of heart rate variability in differentiating patients with and without life-threatening arrhythmias.
The primary source of sulfur dioxide (SO 2 ) emissions is flue gas from fossil fuels-based power plants. SO 2 emissions are known to not only cause health issues, but also have an adverse effect on the environment in various ways. Several Flue Gas Desulfurization (FGD) technologies have been incorporated in power plants. The most popular technology is Wet FGD, where a limestone slurry is used to absorb SO 2 from the flue gas. A detailed droplet scale model describing the instantaneous and finite rate chemistry is developed. The ill-posed Differential-Algebraic Equation (DAE) droplet model is reformulated to a well-posed index-1 DAE through index reduction. The droplet model is integrated with the bulk phase by incorporating gas-liquid mass transfer, and an oxidation reactor model to simulate the dynamic operation of the counter-current spray scrubber. As a result, the model has a well-conditioned Jacobian and overcomes the modeling challenges of previous works and enables numerical solution without requiring carefully selected initialization or specialized solution procedures. The model is successfully validated using power plant measurements, and nonlinear model predictive control (NMPC) studies are demonstrated to optimize recycle stream flowrates to minimize pumping costs.
Astronauts lose bone structure during long-duration spaceflight. These changes are due, in part, to insufficient bone formation by the osteoblast cells. Little is known about the role that small (approximately 22 nucleotide), non-coding micro-RNAs (miRNAs) play in the osteoblast response to microgravity. We hypothesize that osteoblast-lineage cells alter their miRNA status during microgravity exposure, contributing to impaired bone formation during weightlessness. To simulate weightlessness, female mice (C57BL/6, Charles River, 10 weeks of age, n = 6) were hindlimb unloaded for 12 days. Age-matched and normally ambulating mice served as controls (n=6). To assess the expression of miRNAs in skeletal tissue, the right and left tibia of the mice were collected ex vivo and cleaned of soft-tissue and marrow. Total RNA was collected from tibial bone and relative abundance was measured for miRNAs of interest using quantitative real time PCR array looking at 372 unique and well-characterized mature miRNAs using the delta-delta Ct method. Transcripts of interest were normalized to an average of 6 reference RNAs. Preliminary results show that hindlimb unloading decreased the expression of 14 miRNAs to less than 1.4-2.9X control levels and increased the expression of 5 miRNAs relative to the control mice greater than 1-2-1.5X (p less than 0.05, respectively). Using the miRSystem we assessed overlapping target genes predicted to be regulated by multiple members of the 19 differentially expressed miRNAs as well as in silico predicted targets of our individual miRNAs. Our miRSystem results indicated that a number of our differentially expressed miRNAs were regulators of genes related to the Wnt-Beta Catenin pathway-a known regulator of bone health-and, interestingly, the estrogen-mediated cell-cycle regulation pathway, which may indicate that simulated weightlessness induced systemic hormonal changes that contributed to bone loss. We plan to follow up these findings by measuring gene expression of miRNA-regulated genes within these two pathways with the aim of furthering our understanding of the function of miRNAs in the skeletal response to spaceflight.
Several aspects of multigrid methods are briefly described. The main subjects include the development of very efficient multigrid algorithms for systems of elliptic equations (Cauchy-Riemann, Stokes, Navier-Stokes), as well as the development of control and prediction tools (based on local mode Fourier analysis), used to analyze, check and improve these algorithms. Preliminary research on multigrid algorithms for time dependent parabolic equations is also described. Improvements in existing multigrid processes and algorithms for elliptic equations were studied.
Superconductor/metal interfaces are usually fabricated in heterostructures that join these dissimilar materials. A conceptually different approach has recently exploited the strain sensitivity of heavy-fermion superconductors, selectively transforming regions of the crystal into the metallic state by strain gradients. The strain is generated by differential thermal contraction between the sample and the substrate. Here, we present an improved finite-element model that reliably predicts the superconducting transition temperature in CeIrIn 5 even in complex structures. Different substrates are employed to tailor the strain field into the desired shapes. Using this approach, both highly complex and strained as well as strain-free microstructures are fabricated to validate the model. This enables a high degree of control over the microscopic strain fields and forms the basis for more advanced structuring of superconductors as in Josephson junctions yet also finds natural use cases in any material class in which a modulation of the physical properties on a chip is desirable.
Rapid cyclic temperature fluctuation occurring in powder bed fusion of metals using a laser beam (PBF-LB/M) influences the formation of flaws in printed parts. Consequently, there is a pressing need to enhance the quality of printed parts by developing innovative methodologies that can predict thermal histories and help uncover the intricate relationships between process parameters and thermal profiles. Sensitivity Analysis (SA) emerges as an essential tool for this, offering the potential for process optimization and enhanced quality control. Nonetheless, conventional SA methodologies often incur in excessive computational costs and potential numerical approximation errors. Here, to address this technical challenge, we present a novel method for SA that integrates the HYPercomplex-based Automatic Differentiation (HYPAD) technique with transient thermal simulations conducted via the finite element method (FEM). Leveraging this methodology, we efficiently and accurately perform SA for PBF-LB/M processes in a post-processing step. Compared to traditional methods like Finite Differences (FD), HYPAD-FEM required 96 % less computational time for obtaining sensitivities for 22 process parameters, under a comparative study conducted within the context of the 2018–02 AM benchmark of the National Institute of Standards and Technology. In summary, HYPAD-FEM offers superior efficiency and accuracy in SA over conventional methods, delivering the best sensitivity of a model without the need for step-size selection and problem or parameter-based implementations.
Progress in the development of solar heating modular control subsystems is reported. Circuit design, circuit drawings, and printed circuit board layout are discussed along with maintenance manuals, installation instructions, and verification and acceptance tests. Calculations made to determine the predicted performance of the differential thermostat are given including details and results of tests for the offset temperature, and boil and freeze protect points.
Measurements at $\sqrt{s} = 13$ TeV of the opposite-sign W boson pair production cross section in proton-proton collisions are presented. The data used in this study were collected with the CMS detector at the CERN LHC in 2022, and correspond to an integrated luminosity of 34.8 fb -1 . Events are selected by requiring one electron and one muon of opposite charge. A maximum likelihood fit is performed on signal- and background-enriched data categories defined by the flavor and charge of the leptons, the number of jets, and number of jets originating from b quarks. The overall sensitivity is significantly better than that of previous results with a similar integrated luminosity. The improvement comes from a more refined control of experimental uncertainties and an improved fit strategy. An inclusive W + W - production cross section of 125.7 ± 5.6 pb is measured, in agreement with standard model predictions. Cross sections are also reported in a fiducial region close to that of the detector acceptance, both inclusively and differentially, as a function of the jet multiplicity in the event. For the first time in proton-proton collisions, WW events with zero, one, and at least two jets are studied simultaneously and compared with recent theoretical predictions.
A cost-reward model is used to frame a discussion of differences in observed behavior of individuals and groups in confined environments. It has been observed that the high cost of functioning in a stressful environment is likely to produce poor performance when anticipated rewards are low but that participants can manage the stress and achieve high performance if they anticipate high rewards. The high-reward environment is exemplified by early undersea habitats such as Sealab and Tektite and by early space missions. Other aspects of behavior occur in all confined environments and point to an important area for future research. Of particular interest are intergroup conflicts arising between the confined group and its external control. Also, individual differences in personality seem always to have an impact in confined environments. Recent research has focused on: (1) predicting performance and adjustment based on instrumental and expressive aspects of the self; (2) the differential predictive power of achievement striving and irritation/irritability in Type A personalities; and (3) the nature and role of leadership in small, isolated groups.
Abstract Time-dependent SOLPS-ITER simulations have been used to identify reduced models with the sparse identification of nonlinear dynamics (SINDy) method and develop model-predictive control of the boundary plasma state using main ion gas puff actuation. A series of gas actuation sequences are input into SOLPS-ITER to produce a dynamic response in upstream and divertor plasma quantities. The SINDy method is applied to identify reduced linear and nonlinear models for the electron density at the outboard midplane n e , s e p O M P and the electron temperature at the outer divertor T e , s e p d i v . Note that T e , s e p d i v is not necessarily the peak value of T e along the divertor. The identified reduced models are interpretable by construction (i.e. not black box), and have the form of coupled ordinary differential equations. Despite significant noise in T e , s e p d i v , the reduced models can be used to predict the response over a range of actuation levels to a maximum deviation of 0.5% in n e , s e p O M P and 5%–10% in T e , s e p d i v for the cases considered. Model retraining using time history data triggered by a preset error threshold is also demonstrated. A model predictive control strategy for nonlinear models is developed and used to perform feedback control of a SOLPS-ITER simulation to produce a setpoint trajectory in n e , s e p O M P using the integrated plasma simulator framework. The developed techniques are general and can be applied to time-dependent data from other boundary simulations or experimental data. Ongoing work is extending the approach to model identification and control for divertor detachment, which will present transient nonlinear behavior from impurity seeding, including realistic latency and synthetic diagnostic signals derived from the full SOLPS-ITER output.
An investigation was carried out to assess the accuracy of a transitional boundary layer theory in the low hypersonic Mach number regime. The theory is based upon the simultaneous numerical solution of the boundary layer partial differential equations for the mean motion and an integral form of the turbulence kinetic energy equation which controls the magnitude and development of the Reynolds stress. Comparisions with experimental data show the theory is capable of accurately predicting heat transfer and velocity profiles through the transitional regime and correctly predicts the effects of Mach number and wall cooling on transition Reynolds number. The procedure shows promise of predicting the initiation of transition for given free stream disturbance levels. The effects on transition predictions of the pressure dilitation term and of direct absorption of acoustic energy by the boundary layer were evaluated.
Focal Area: (2) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization. We emphasize the importance of leveraging optimization techniques from AI/machine learning (ML) to solve challenging problems in Earth system modeling. Science Challenge: Automatic differentiation has had a transformative effect on ML by allowing the calculation of gradients of arbitrary functions in an incredibly large class of models. We can potentially realize similar improvements in parameter estimation and control for Earth system models (ESMs) by reimplementing them in computational frameworks from ML. Practitioners working with large (>10 7 parameters) models in ML and AI can obtain good predictive performance in a range of spatiotemporal tasks by making use of optimization via stochastic gradient descent and incorporating prior knowledge at multiple levels. We propose writing ESMs in open-source computational frameworks such as Torch, Tensorflow, and JAX to greatly expand the scope of environmental forecasting and management challenges, which can be addressed by leveraging automatic differentiation and gradient descent-like algorithms. We do not call for a wholesale replacement of physical models with data-driven surrogates, but rather advocate for interleaving physical and empirical equations in a manner that is most faithful to the extent of our scientific knowledge and observational data. Central to this topic is the merging of differentiable physical simulations with differentiable optimization layers, which are now both beginning to come to the forefront.