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Purpose: Sleep loss and alcohol have been shown to impair smooth pursuit and its underlying visual motion processing in humans. This study examines the saccadic compensation for this poor pursuit. Methods: Using an established behavioral ocular-tracking paradigm (Liston & Stone, 2014, doi:10.1167/14.14.12), we examined the dose-response of ground lost (pursuit deficit integrated across our 300-ms steady-state tracking interval) and ground gained (increased saccadic response harnessed to compensate)across three separate studies – acute low-dose alcohol administration (LDA; n = 16 subjects), acute sleep loss(ASL; n = 12), and chronic sleep restriction (CSR; n = 12). We computed dose-responses as the linear regression slopes of ground lost and gained across treatment dose (% blood alcohol concentration [BAC] or hours awake). For the CSR study, we computed the mean effect for a single dose (5-hours nightly sleep for 1week). Results: For LDA, there was significantly increased ground lost (P < 0.001) and gained (P < 0.001) with increased %BAC. In addition, the dose-responses were not significantly different (P = 0.35), indicating effectively complete saccadic compensation due to significant increases in both saccadic rate (P < 0.05) and amplitude (P < 0.001). For ASL, there was significantly increased ground lost with time awake (P < 0.01),however ground gained was significantly lower (P < 0.001), indicating, at best, incomplete compensation due to a significant increase in saccadic rate (P < 0.001) but not amplitude (P = 0.10). With CSR, pursuit was again significantly impaired (P < 0.05), with saccadic rate significantly increased (P < 0.05) but, surprisingly, amplitude was significantly decreased (P < 0.05), effectively eliminating ground gained (P = 0.90). Conclusions: Our analyses show that LDA, ASL, and CSR affect tracking differently, suggesting the involvement of different brain pathways. With LDA, the effect appears largely due to the cortical impairment of visual motion processing with largely healthy brainstem and mid-brain responses (driving effective saccadic compensation). ASL and CSR however appear to affect both cortical and sub-cortical pathways, with at best partial saccadic compensation. Lastly, CSR is associated with an additional compromise due to a maladaptive decrease in saccade amplitude.
Use of probability of collision (Pc) has brought sophistication to CA. Made possible by JSpOC precision catalogue because provides covariance. Has essentially replaced miss distance as basic CA parameter. Embrace of Pc has elevated methods to 'manipulate' covariance to enable/improve CA calculations. Two such methods to be examined here; compensation for absent or unreliable covariances through 'Maximum Pc' calculation constructs, projection (not propagation) of epoch covariances forward in time to try to enable better risk assessments. Two questions to be answered about each; situations to which such approaches are properly applicable, amount of utility that such methods offer.
Since the characteristics of the industrial heat exchange system (HES) are drastically affected by variations of the steam pressure, ambient temperature and water quality, it is difficult for the classical cascade PI control system to meet the desirable control objectives. Therefore, in this paper, a deterministic linear model with unmodeled dynamics is used to describe the dynamic characteristics of the HES. It should be noted that the unmodeled dynamics at the previously sampled instant can be calculated using actual measurements and that the tracking error, which includes effects of the rate of changes of unmodeled dynamics on the controlled model, can be accurately determined. An additional compensating signal is obtained with the feedforward control together with a one-step optimal control law. Consequently, the cascade PI control strategy with the signal compensation is established. Furthermore, the simulation and industrial application show that the proposed method can effectively improve the performance of the cascade PI control system, especially when the unmodeled dynamics is subjected to unknown variations.
For fused magnesia smelting processes, the proportional-integral-derivative (PID) controller is difficult to regulate the smelting currents within desired ranges due to unexpected variations of the dynamics caused by material feeding operations. To solve this problem, we first proposed its dynamic model composed of a linear model and an uncertain nonlinear dynamic system that describes the unknown time-varying dynamics of nonlinearity and strong couplings among controlled variables. Then, using the accurately calculated value of the uncertain part at the previous sampling time instant and the tracking error that reflects the influence of its change rate, we developed a feedforward and a one-step optimal control to obtain two signal compensators to eliminate the impact of frequent variations of the uncertainties. For the compensators, we proposed a weight selection method to minimize the sum of the squared tracking error with ensured closed-loop stability. Based on the abovementioned modeling and control structure, we finally developed a novel adaptive PID controller augmented with signal compensators to control the whole process. Industrial applications have shown that the proposed method can always keep the tracking error and the control input within their targeted ranges, leading to a significantly reduced energy consumption per ton and increased fused magnesia production.
A compensated dynamic gas temperature thermocouple measurement method was experimentally verified. Dynamic gas temperature signals from a flow passing through a chopped-wheel signal generator and an atmospheric pressure laboratory burner were measured by the dynamic temperature sensor and other fast-response sensors. Compensated data from dynamic temperature sensor thermoelements were compared with fast-response sensors. Results from the two experiments are presented as time-dependent waveforms and spectral plots. Comparisons between compensated dynamic temperature sensor spectra and a commercially available optical fiber thermometer compensated spectra were made for the atmospheric burner experiment. Increases in precision of the measurement method require optimization of several factors, and directions for further work are identified.
Past research at the Advanced Light Source (ALS) provided a proof-of-principle demonstration that deep learning methods could be effectively employed to compensate for the significant perturbations to the transverse electron beam size induced by user-controlled adjustments of the insertion devices. However, incorporating these methods into the ALS’ daily operations has faced notable challenges. The complexity of the system’s operational requirements and the significant upkeep demands has restricted their sustained application during user operation. Here, we introduce the development of a more robust neural network (NN)-based algorithm that utilizes a novel online fine-tuning approach and its systematic integration into the day-to-day machine operations. Our analysis emphasizes the process of NN model selection, demonstrates the superior performance of the NN-based method over traditional feedback methods, and examines the effectiveness and resilience of the new algorithm during user-operation scenarios. Published by the American Physical Society 2024
The center-to-center spacings of a photoresist pattern for an array of holes applied to a thin metal sheet are increased by uniformly stretching the thin metal sheet in all directions along the plane of the sheet. The uniform stretching is provided by securely clamping the periphery of the sheet and applying an annular force against the face of the sheet, within the periphery of the sheet and around the photoresist pattern. The technique is used in the construction of ion thruster grid units where the outer or downstream grid is subjected to uniform stretching prior to convex molding. The technique provides alignment of the holes of grid pairs so as to direct the ion beamlets in a direction parallel to the axis of the grid unit and thereby provide optimization of the available thrust.
A method based on complementary filtering is shown to be effective in compensating for the image stabilization error due to sampling delays of HMD position and orientation measurements. These delays would otherwise have prevented the stabilization of the image in HMDs. The method is also shown to improve the resolution of the head orientation measurement, particularly at low frequencies, thus providing smoother head control commands, which are essential for precise head pointing and teleoperation.
The high pressure and high strain rate dynamic strength of Mo is experimentally and computationally investigated in the 3–20 GPa stress, 50–600 C temperature, and 10 5 –10 6 /s strain rate regimes using a modified tamped Richtmyer-Meshkov instability (RMI) method. Modifications to the tamped RMI method include a method to determine loading states during strain, a new strength calibration function based on interface shape, and a robust uncertainty quantification method. These modifications improve fidelity of the tamped RMI method, allowing evaluation of the compensating effects of pressure hardening, strain rate hardening, strain hardening, and thermal softening. The new calibration function based on interface shape is not limited to sinusoidal corrugations and could be applied to additional interface shapes. Plate impact experiments are performed at Argonne National Laboratory’s Advanced Photon Source’s Dynamic Compression Sector operated by Washington State University (DCS), driving a planar shock front through a corrugated Mo-D 2 O or Mo-C 8 F 18 interface, forcing the corrugation to significantly deform. The extent of interfacial deformation, RMI growth, is experimentally observed using X-ray phase contrast imaging at the DCS. RMI jet lengths and jet shapes are extracted from the experimental radiographs, then used to calibrate numerical simulations performed with the Sandia National Laboratories (SNL) hydrocode CTH. Mo yield strength, Y, as a function of shock pressure, P, strain rate, $\dot{\varepsilon }$, accumulated strain, ϵ, relative volumetric compression, RD , and temperature, T , is determined for each impact experiment and presented. The calibrated Mo yield strength values range 1.2–1.8 GPa, with strength generally decreasing as the impact stress increases. This trend is likely caused by thermal softening or strain localization. The tabular yield strength versus loading condition data presented in this paper can be used to fit complex strength models.
Battery charge control for orbiting spacecraft with mission durations from three to ten years, is a critical design feature that is discussed. Starting in 1974, the General Electric Space Systems Division designed, manufactured and tested battery systems for six different space programs. Three of these are geosynchronous missions, two are medium altitude missions and one is a near-earth mission. All six power subsystems contain nickel cadmium batteries which are charged using a temperature compensated voltage limit. This charging method was found to be successful in extending the life of nickel cadmium batteries in all three types of earth orbits. Test data and flight data are presented for each type of orbit.
Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.
Data fusion and sensor management approaches have largely been implemented with centralized and hierarchical architectures. Numerical and statistical methods are the most common data fusion methods found in these systems. Given the proliferation and low cost of processing power, there is now an emphasis on designing distributed and decentralized systems. These systems use analytical/quantitative techniques or qualitative reasoning methods for date fusion.Based on other work by the author, a sensor may be treated as a highly autonomous (decentralized) unit. Each highly autonomous sensor (HAS) is capable of extracting qualitative behaviours from its data. For example, it detects spikes, disturbances, noise levels, off-limit excursions, step changes, drift, and other typical measured trends. In this context, this paper describes a distributed sensor fusion paradigm and theory where each sensor in the system is a HAS. Hence, given the reach qualitative information from each HAS, a paradigm and formal definitions are given so that sensors and processes can reason and make decisions at the qualitative level. This approach to sensor fusion makes it possible the implementation of intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors. This paradigm facilitates a balanced distribution of intelligence (code and/or hardware) to the sensor level, the process/system level, and a higher controller level. The primary application of interest is in intelligent health management of rocket engine test stands.
This is the final report for this project. The major objectives were to develop full models and standard cells of CMOS silicon photomultipliers (SiPM) for neutron detection applications. Specifically, the research seeks to replace photomultiplier tubes, used in neutron detection applications, with SiPMs containing integrated readout electronics fabricated in standard CMOS processes. The detectors improve on the detection efficiency, readout speed, resolution (sensitivity), and spatial resolution of current systems. In particular, this work involved collaboration with the instrument and detector group at ORNL who build detectors based on discrete commercially available PMTs and SiPMs. The SiPM detectors developed in this work are based on Perimeter Gated Single Photon Avalanche Diodes (PGSPAD). These devices have tunable breakdown voltage which affects other performance characteristics of the detectors. The ability of the detectors to have integrated readout and tune the noise floor and dynamic range in addition to offering a method for non-uniformity compensation in a compact form significantly impacts the imaging research field and includes the nuclear sciences field, circuits and systems field in addition to varied fields such as geography and biology/medicine.
Colloidal semiconductor nanocrystals are considered promising materials for high-flux optical applications, including lasing, light-emitting diodes, biological imaging, and quantum optics. In high-flux applications, multiexcitons can significantly contribute to emission, influencing its brightness, spectral purity, and kinetics. As a result, understanding and controlling multiexciton emission in colloidal nanocrystal materials is of the utmost importance. In the past, single-nanocrystal photon correlation methods have been applied to understand biexciton and triexciton efficiencies, lifetimes, and spectra. While powerful, such methods suffer from user selection bias and require stable emission from single nanocrystals. To compensate for this shortcoming, second-order correlation methods were developed to extract sample-averaged biexciton properties from a solution of nanocrystals. Until now, however, the analogous third-order solution photon correlation methods remained unexplored. In this work, we present a pair of third-order photon correlation techniques to obtain the sample-averaged single-nanocrystal triexciton quantum yield and lifetime in a solution-phase experiment. These techniques derive from the relationship between the Poisson probability of nanocrystal photon absorption and the intrinsic probability of nanocrystal photon emission. We validate the theoretical background of these techniques by creating a numerical model to simulate the diffusion and emission of many nanocrystals in solution. Our simulations confirm that the average triexciton quantum yield and triexciton lifetime can be extracted from a solution of nanocrystals. These techniques will enable researchers to gain a better understanding of the fundamental multiexciton properties of colloidal nanocrystals.
Dissolved organic matter (DOM) is widely recognized to control the solubility and reactivity of trace metals in the environment. However, the mechanisms that govern metal-DOM complexation remain elusive, primarily due to the analytical challenge of fractionating and quantifying metal–organic species within the complex mixture of organic compounds that comprise DOM. Here, we describe a quantitative method for fractionation and element-specific detection of organic–metal complexes using liquid chromatography with online inductively coupled plasma mass spectrometry (LC–ICP-MS). The method implements a post-column compensation gradient to stabilize ICP–MS elemental response across the LC solvent gradient, thereby overcoming a major barrier to achieving quantitative accuracy with LC–ICP-MS. With external calibration and internal standard correction, the method yields concentrations of organic–metal complexes that were consistently within 6% of their true values, regardless of the complex’s elution time. We used the method to evaluate the effects of four stationary phases (C18, phenyl, amide, and pentafluoroylphenyl propyl) on the recovery and separation of environmentally relevant trace metals (Mn, Fe, Co, Ni, Cu, Zn, Cd, and Pb) in Suwannee River Fulvic Acid and Suwannee River Natural Organic Matter. The C18, amide, and phenyl phases generally yielded optimal metal recoveries (>75% for all metals except Pb), with the phenyl phase separating polar species to a greater extent than C18 or amide. We also fractionated organic-bound Fe, Cu, and Ni in oxidized and reduced soils, revealing divergent metal-DOM speciation across soil redox environments. Finally, by enabling quantitative fractionation of DOM-bound metals, our method offers a means for advancing a mechanistic understanding of metal–organic complexation throughout the environment.
A thermal oxide patterning method has proven to be effective for correcting coating-stress-induced distortion on flat silicon wafers. We report progress on developing this method for correcting curved silicon mirrors distorted by front-side iridium coatings. Owing to the difference in geometry, a finite element model has been established to calculate the appropriate duty cycle maps in thermal oxide hexagon patterns used for compensation. In addition, a photolithographic process, along with three-dimensional printed equipment, has been developed for creating patterns precisely on the back side of curved mirrors. The developed method has been used to recover the original surface shape of two silicon mirrors which are 100-mm long, 0.5-mm thick, having 312-mm radius of curvature, and 30 deg in azimuthal span (Wolter-I geometry). These mirrors’ front sides are sputter-coated by 20-nm iridium layers with ∼-70 N∕m integrated stress. Measurement results show that the developed method can mitigate coating-induced distortion by a factor of ∼5 in RMS height and ∼4 in RMS slope error, corresponding to ∼0.5 arc sec RMS slope error. Residual errors after correction are dominated by midfrequency ripples created during the annealing process, which will be resolved in the future. The presented method is precise and inexpensive and a potential candidate for resolving the coating stress issue for Lynx optics in the future.