An application of the square root information filter to large-scale linear interconnected systems
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Bierman, G. J.↗
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Super resolution for root imaging
Premise High‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection. An effective super‐resolution (SR) algorithm is therefore needed for overcoming the resolution limitations of sensors, reducing storage space requirements, and boosting the performance of subsequent analyses. Methods We propose an SR framework for enhancing images of plant roots using convolutional neural networks. We compare three alternatives for training the SR model: (i) training with non‐plant‐root images, (ii) training with plant‐root images, and (iii) pretraining the model with non‐plant‐root images and fine‐tuning with plant‐root images. The architectures of the SR models were based on two state‐of‐the‐art deep learning approaches: a fast SR convolutional neural network and an SR generative adversarial network. Results In our experiments, we observed that the SR models improved the quality of low‐resolution images of plant roots in an unseen data set in terms of the signal‐to‐noise ratio. We used a collection of publicly available data sets to demonstrate that the SR models outperform the basic bicubic interpolation, even when trained with non‐root data sets. Discussion The incorporation of a deep learning–based SR model in the imaging process enhances the quality of low‐resolution images of plant roots. We demonstrate that SR preprocessing boosts the performance of a machine learning system trained to separate plant roots from their background. Our segmentation experiments also show that high performance on this task can be achieved independently of the signal‐to‐noise ratio. We therefore conclude that the quality of the image enhancement depends on the desired application.
Ruiz‐Munoz, Jose F.↗
Performance of Swashplateless Ultralight Helicopter Rotor with Trailing-edge Flaps for Primary Flight Control
The objective of present study is to evaluate the rotor performance, trailing-edge deflections and actuation requirement of a helicopter rotor with trailing-edge flap system for primary flight control. The swashplateless design is implemented by modifying a two-bladed teetering rotor of an production ultralight helicopter through the use of plain flaps on the blades, and by replacing the pitch link to fixed system control system assembly with a root spring. A comprehensive rotorcraft analysis based on UMARC is carried out to obtain the results for both the swashplateless and a conventional baseline rotor configuration. The predictions show swashplateless configuration achieve superior performance than the conventional rotor attributed from reduction of parasite drag by eliminating swashplate mechanic system. It is indicated that optimal selection of blade pitch index angle, flap location, length, and chord ratio reduces flap deflections and actuation requirements, however, has virtually no effect on rotor performance.
Shen, Jin-Wei↗
Wheat production in controlled environments
Conditions are optimized for maximum yield and quality of wheat to be used in a controlled environment life support system (CELSS) in a Lunar or Martian base or a spacecraft. With yields of 23 to 57 g/sq m/d of edible biomass, a minimum size for a CELSS would be between 12 and 30 sq m per person, utilizing about 600 W/sq m of electrical energy for artificial light. Temperature, irradiance, photoperiod, carbon dioxide levels, humidity, and wind velocity are controlled in growth chambers. Nutrient solutions (adjusted for wheat) are supplied to the roots via a recirculating system that controls pH by adding HNO3 and controlling the NO3/NH4 ratio in solution. A rock-wool plant support allows direct seeding and densities up to 10,000 plants sq m. Densities up to 2000 plants/sq m appear to increase seed yield. Biomass production increases almost linearily with increasing irradiance from 400 to 1700 micromol/sq m/s of photosynthetic photon flux, but the efficiency of light utilization decreases over this range. Photoperiod and temperature both have a profound influence on floral initiation, spikelet formation, stem elongation, and fertilization.
Salisbury, Frank B.↗
Coincident learning for beam-based rf station fault identification using phase information at the SLAC linac coherent light source
Anomalies in radio-frequency (rf) stations can result in unplanned downtime and performance degradation in linear accelerators such as SLAC’s Linac Coherent Light Source (LCLS). Detecting these anomalies is challenging due to the complexity of accelerator systems, high data volume, and scarcity of labeled fault data. Prior work identified faults using beam-based detection, combining rf amplitude and beam position monitor data. Due to the simplicity of the rf amplitude data, classical methods are sufficient to identify faults, but the recall is constrained by the low-frequency and asynchronous characteristics of the data. In this work, we leverage high-frequency, time-synchronous rf phase data to enhance anomaly detection in the LCLS accelerator. Due to the complexity of phase data, classical methods fail, and we instead train deep neural networks within the Coincident Anomaly Detection (CoAD) framework. We find that applying CoAD to phase data detects nearly 3 times as many anomalies as when applied to amplitude data, while achieving broader coverage across rf stations. Furthermore, the rich structure of phase data enables us to cluster anomalies into distinct physical categories. Through the integration of auxiliary system status bits, we link clusters to specific fault signatures, providing additional granularity for uncovering the root cause of faults. We also investigate interpretability via Shapley values, confirming that the learned models focus on the most informative regions of the data and providing insight for cases where the model makes mistakes. This work demonstrates that phase-based anomaly detection for rf stations improves both diagnostic coverage and root cause analysis in accelerator systems and that deep neural networks are essential for effective analysis.
Accelerator Physics (physics.acc-ph)↗
Phytochromes A and B mediate red-light-induced positive phototropism in roots
The interaction of tropisms is important in determining the final growth form of the plant body. In roots, gravitropism is the predominant tropistic response, but phototropism also plays a role in the oriented growth of roots in flowering plants. In blue or white light, roots exhibit negative phototropism that is mediated by the phototropin family of photoreceptors. In contrast, red light induces a positive phototropism in Arabidopsis roots. Because this red-light-induced response is weak relative to both gravitropism and negative phototropism, we used a novel device to study phototropism without the complications of a counteracting gravitational stimulus. This device is based on a computer-controlled system using real-time image analysis of root growth and a feedback-regulated rotatable stage. Our data show that this system is useful to study root phototropism in response to red light, because in wild-type roots, the maximal curvature detected with this apparatus is 30 degrees to 40 degrees, compared with 5 degrees to 10 degrees without the feedback system. In positive root phototropism, sensing of red light occurs in the root itself and is not dependent on shoot-derived signals resulting from light perception. Phytochrome (Phy)A and phyB were severely impaired in red-light-induced phototropism, whereas the phyD and phyE mutants were normal in this response. Thus, PHYA and PHYB play a key role in mediating red-light-dependent positive phototropism in roots. Although phytochrome has been shown to mediate phototropism in some lower plant groups, this is one of the few reports indicating a phytochrome-dependent phototropism in flowering plants.
NASA Discipline Plant Biology↗
Application of AI techniques to infer vegetation characteristics from directional reflectance(s)
Traditionally, the remote sensing community has relied totally on spectral knowledge to extract vegetation characteristics. However, there are other knowledge bases (KB's) that can be used to significantly improve the accuracy and robustness of inference techniques. Using AI (artificial intelligence) techniques a KB system (VEG) was developed that integrates input spectral measurements with diverse KB's. These KB's consist of data sets of directional reflectance measurements, knowledge from literature, and knowledge from experts which are combined into an intelligent and efficient system for making vegetation inferences. VEG accepts spectral data of an unknown target as input, determines the best techniques for inferring the desired vegetation characteristic(s), applies the techniques to the target data, and provides a rigorous estimate of the accuracy of the inference. VEG was developed to: infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; infer percent ground cover from any combination of nadir and/or off-nadir view angles; infer unknown view angle(s) from known view angle(s) (known as view angle extension); and discriminate between user defined vegetation classes using spectral and directional reflectance relationships developed from an automated learning algorithm. The errors for these techniques were generally very good ranging between 2 to 15% (proportional root mean square). The system is designed to aid scientists in developing, testing, and applying new inference techniques using directional reflectance data.
Kimes, D. S.↗
Data from TropiRoot 1.0 database: tropical root characteristics across environments
TropiRoot 1.0 is a new tropical root database with root characteristics across environment gradients. It has data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 includes root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology and root chemistry. This initiative represents an approximately 30% increase in the currently available data for tropical roots in the Fine Root Ecology Database (FRED). TropiRoot 1.0, contains root characteristics from 25 different countries where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data was available, including soil data, these data was either extracted and included in the database or their availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match the ones reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions, and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models.
54 ENVIRONMENTAL SCIENCES↗
Control of Initialized Fractional-Order Systems
Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex Airplane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex Airplane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.
Hartly, Tom T.↗
Control of Initialized Fractional-Order Systems
Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex w-plane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex w-plane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.
Hartley, Tom T.↗
Seam tracking performance of a Coaxial Weld Vision System and pulsed welding
This report describes a continuation of a series of tests on the Coaxial Weld Vision System at MSFC. The ability of the system to compensate for transients associated with pulsed current welding is analyzed. Using the standard image processing approach for root pass seam tracking, the system is also tested for the ability to track the toe of a previous weld bead, for tracking multiple pass weld joints. This Coaxial Weld Vision System was developed by the Ohio State University (OSU) Center for Welding Research and is a part of the Space Shuttle Main Engine Robotic Welding Development System at MSFC.
Gangl, K. J.↗
Smart connected worker edge platform for smart manufacturing: Part 2—Implementation and on‐site deployment case study
Abstract In this paper, we describe specific deployments of the Smart Connected Worker (SCW) Edge Platform for Smart Manufacturing through implementation of four instructive real‐world use cases that illustrate the role of people in a Smart Manufacturing paradigm through which affordable, scalable, accessible, and portable (ASAP) information technology (IT) acquires and contextualizes data into information for transmission to operation technologies (OT). For case one, the platform captures the relationships between energy consumption and human workflows for improved energy productivity while workers interact with machines during semiconductor manufacturing. The platform utilizes human cognition to identify anomalous machine behavior for root cause analysis of system faults via neural network (NN) that recognize alarm postures of workers with cameras. For case two, a smart assembly line is demonstrated for state monitoring and fault detection. Machine learning (ML) models are used to recognize system states and identify fault scenarios with human intervention. For case three, the platform monitors human–machine interactions to classify manufacturing machine states for proper operations and energy productivity. Internal energy states of individual or collections of manufacturing equipment are determined via NN based algorithms that disaggregate signals associated with smart metering typically deployed at manufacturing facilities. These methods predict the real time energy profile of each machine from the total energy profile of a manufacturing site. For case four, a software defined sensor system built with scientific workflow engines is demonstrated for contextualizing data from laser surface refraction for characterization, and diagnostics in the processing of additively manufactured titanium alloy.
Donovan, Richard P.↗
Optimizing Selection Pressures and Pest Management to Maximize Cultivation Yield (OSPREY) (Final Technical Report)
This project was proposed in response to AOI 1, Cultivation Intensification Processes for Algae, within the FY19 Bioenergy Technologies Office Multi-Topic Funding Opportunity Announcement (FOA Number: DE-FOA-0002029). The work was designed to address a critical industry need to improve annualized productivity, stability, and quality of algal production strains for biofuels and bioproducts. The overall project goals were to generate process innovations rooted in established outdoor systems for strain selection, improvement, maintenance, and cultivation as well as pest detection and tracking. Planned advances included a 50% improvement in harvest yield based on AFDW (g m 2 d -1 ), 50% improvement in robustness based on stability metrics (e.g., high-productivity cultivation days, pond uptime), and 20% improvement in conversion yield. Individually, each of our planned process improvements (e.g., pest tracking) had the potential to increase productivity. However, to realize increases in yield at the system level, improvements to one unit’s process must be balanced against potential effects on other processes. For example, changes to strains, cultivation, and pest management developed in isolation may hurt other unit operations. Therefore, a critical success factor of the project was the integration of the pipeline components, achieved through iterative field-to- (short term) lab testing. In addition, through sustainability models, we evaluated how improvements would alter industry scenarios.
09 BIOMASS FUELS↗
Linear systems analysis program, L224(QR). Volume 2: Supplemental system design and maintenance document
The computer program known as QR is described. Classical control systems analysis and synthesis (root locus, time response, and frequency response) can be performed using this program. Programming details of the QR program are presented.
Heidergott, K. W.↗
Linear systems analysis program, L224(QR). Volume 1: Engineering and usage
The QR computer program is described as well as its use in classical control systems analysis and synthesis (root locus, time response, and frequency response).
Shah, P. C.↗
On the control and stability of the pinhole occulter flexible boom facility
The dynamics and control of the Shuttle based, gimbal mounted, boom pointing system for use in the X-ray pinhole experiments were studied. The overall system stability was studied, and root locus compensation was designed to achieve stability and pointing stability requirements. This single axis control study found the compensated system to be stable and capable of pointing to within 6.5 arc sec while the Shuttle rocks in its 0.1 deg deadband. The system follows step (positon) inputs with zero error and rupm (velocity) inputs with a steady state error coefficient of 4.5/sec.
Greene, M.↗
A research program in active control/aeroelasticity in the JIAFS at NASA Langley Research Center
A control law synthesis methodology for multifunctional active control system to satisfy root-mean-square load and response constraints as well as to meet stability robustness requirements at plant input and output was developed. Modern control theory, singular value analysis and optimization techniques were utilized. All stability and response derivative expressions were derived analytically for sensitivity study. The software is incorporated as an update to the AB/LAD general control design software package PADLOCS.
Whitesides, J. L.↗
Subclinical Shed of Infectious Varicella zoster Virus in Astronauts
Aerosol borne varicella zoster virus (VZV) enters the nasopharynx and replicates in tonsillar T-cells, resulting in viremia and varicella (chickenpox). Virus then becomes latent in cranial nerve, dorsal root and autonomic nervous system ganglia along the entire neuraxis (1). Decades later, as cell-mediated immunity to VZV declines (4), latent VZV can reactivate to produce zoster (shingles). Infectious VZV is present in patients with varicella or zoster, but shed of infectious virus in the absence of disease has not been shown. We previously detected VZV DNA in saliva of astronauts during and shortly after spaceflight, suggesting stress induced subclinical virus reactivation (3). We show here that VZV DNA as well as infectious virus in present in astronaut saliva. VZV DNA was detected in saliva during and after a 13-day spaceflight in 2 of 3 astronauts (Fig. panel A). Ten days before liftoff, there was a rise in serum anti-VZV antibody in subjects 1 and 2, consistent with virus reactivation. In subject 3, VZV DNA was not detected in saliva, and there was no rise in anti-VZV antibody titer. Subject 3 may have been protected from virus reactivation by having zoster <10 years ago, which provides a boost in cell-medicated immunity to VZV (2). No VZV DNA was detected in astronaut saliva months before spaceflight, or in saliva of 10 age/sex-matched healthy control subjects sampled on alternate days for 3 weeks (88 saliva samples). Saliva taken 2-6 days after landing from all 3 subjects was cultured on human fetal lung cells (Fig. panel B). Infectious VZV was recovered from saliva of subjects 1 and 2 on the second day after landing. Virus specificity was confirmed by antibody staining and DNA analysis which showed it to be VZV of European descent, common in the US (5). Further, both antibody staining and DNA PCR demonstrated that no HSV-1 was detected in any infected culture. This is the first report of infectious VZV shedding in the absence of clinical disease. Spaceflight presents a uniquely stressful environment which includes physical isolation and confinement, anxiety, sleep deprivation, as well as exposure to increased radiation and microgravity. It is interesting that in our study, VZV and not HSV-1 reactivation was detected, since stress-induced HSV-1 reactivation has been reported (6). Future studies are needed to determine the specific inducer of VZV reactivation.
Cohrs, Randall J.↗