X-15 Data Display System
Digital data processing techniques for conversion of physiological and environmental response signals from X-15 aircraft pilots
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Digital data processing techniques for conversion of physiological and environmental response signals from X-15 aircraft pilots
A method of motion control for robotics and other automatically controlled machinery using a neural network controller with real-time environmental feedback. The method is illustrated with a two-finger robotic hand having proximity sensors and force sensors that provide environmental feedback signals. The neural network controller is taught to control the robotic hand through training sets using back- propagation methods. The training sets are created by recording the control signals and the feedback signal as the robotic hand or a simulation of the robotic hand is moved through a representative grasping motion. The data recorded is divided into discrete increments of time and the feedback data is shifted out of phase with the control signal data so that the feedback signal data lag one time increment behind the control signal data. The modified data is presented to the neural network controller as a training set. The time lag introduced into the data allows the neural network controller to account for the temporal component of the robotic motion. Thus trained, the neural network controlled robotic hand is able to grasp a wide variety of different objects by generalizing from the training sets.
Superposition testing of detection range performance forms a digital signal for input into a simulation of signal and data processing equipment and algorithms to be employed in a sensor system for advanced warning of hazardous windshear. For suitable pulse-Doppler radar, recording of the digital data at the input to the digital signal processor furnishes a realistic operational scenario and environmentally responsive clutter signal including all sidelobe clutter, ground moving target indications (GMTI), and large signal spurious due to mainbeam clutter and/or RFI respective of the urban airport clutter and aircraft scenarios (approach and landing antenna pointing). For linear radar system processes, a signal at the same point in the process from a hazard phenomena may be calculated from models of the scattering phenomena, for example, as represented in fine 3 dimensional reflectivity and velocity grid structures. Superposition testing furnishes a competing signal environment for detection and warning time performance confirmation of phenomena uncontrollable in a natural environment.
The procedures to be followed in assessing the performance of the MOS color camera are defined. Aspects considered include: horizontal and vertical resolution; value of the video signal; gray scale rendition; environmental (vibration and temperature) tests; signal to noise ratios; and white balance correction.
The present disclosure relates to an adaptive, free-space optical system. The system may have a controller and a digital micromirror (DMM) array responsive to the controller. The digital micromirror may include a plurality of independently controllable micromirror elements forming a receiver for receiving optical signals from an environmental scene. At least two of the plurality of independently controllable micromirror elements are steerable in different directions to receive optical signals emanating from two or more locations within the environmental scene. A beam steering subsystem forms a portion of the micromirror array and is in communication with the controller for receiving control signals from the controller. A detector is used to receive an incoming free space optical signal imaged by at least one of the micromirror elements.
Time and frequency (T and F) are fundamental and pervasive parameters of telecommunication technology. Advancing development of digital communications using data modulation rates above 2400 baud and time-division multiplex in complex network configurations is now requiring more accurate and precise T and F reference information for efficient operation of telecommunication systems. A schematic diagram of a general communication system is shown. This diagram is very general and can depict any type of communication. The information source selects a specific message which is encoded and sent through a communication channel. Enroute, the signal is subjected to perturbations from environmental noise. The received signal is then decoded and delivered to its destination. Through the process, the message may undergo many spurious changes, resulting in a loss of information content in the delivered message as compared to the original selected message. In digital telecommunication systems, loss of information content of the signals can be attributed to noise, distortion of waveshape, and loss of synchronization.
Distributed acoustic sensing (DAS) has a demonstrated potential for wide-scale and continuous in situ monitoring of near-surface environmental and anthropogenic processes. DAS is attractive for development as a multi-geophysical observatory due to the prevalence of existing fiber infrastructure in regions with environmental, cultural, or strategic significance. To evaluate the efficacy of this technology for monitoring of polar environmental processes, we collected DAS data from a 37-km long section of seafloor telecommunications fiber located on the continental shelf of the Beaufort Sea, Alaska. This experiment spanned eight, one-week, seasonally-distributed periods across two years. This was the first ever deployment of seafloor DAS beneath sea ice, and the first deployment in any marine environment to span multiple seasons. We recorded a variety of environmental and anthropogenic signals with demonstrable utility for the study of sea ice dynamics and tracking of ocean vessels and ice-traversing vehicles.
Microbial existence and survival requires the ability to sense and respond to environmental changes, including changes in physical forces. This is because microbes inhabit an amazingly diverse range of ecological niches and therefore must constantly adapt to a wide variety of changing environmental conditions, including alterations in temperature, pH, nutrient availability, oxygen levels, and osmotic pressure gradients. Microbes sense their environment through a variety of sensors and receptors which serve to integrate the different signals into the appropriate cellular response(s) that is optimal for survival. While numerous environmental stimuli have been examined for their effect on microorganisms, effects due to changes in mechanical and/or physical forces are also becoming increasingly apparent. Recently, several important studies have demonstrated a key role for microgravity and the low fluid shear dynamics associated with microgravity in the regulation of microbial gene expression, physiology and pathogenesis. The mechanosensory response of microorganisms to these environmental signals, which are relevant to those encountered during microbial life cycles on Earth, may provide insight into their adaptations to physiologically relevant conditions and may ultimately lead to eludicidation of the mechanisms important for mechanosensory transduction in living cells. This review summarizes the recent and potential future research trends aimed at understanding the effect of changes in mechanical forces that occur in microgravity and other low shear environments on different microbial parameters. The results of these studies provide an important step towards understanding how microbes integrate information from multiple mechanical stimuli to an appropriate physiological response.
This study presents a comparative evaluation of post-process sensor integration in additively manufactured (AM) metal and the in-situ process for polymer structures for structural health monitoring (SHM), with an emphasis on embedded sensors. Geometrically identical specimens were fabricated using copper via metal fused filament fabrication (FFF) and PLA via polymer FFF, with piezoelectric transducers (PZTs) inserted into internal cavities to assess the influence of material and placement on sensing fidelity. Mechanical testing under compressive and point loads generated signals that were transformed into time–frequency spectrograms using a Short-Time Fourier Transform (STFT) framework. An engineered RGB representation was developed, combining global amplitude scaling with an amplitude-envelope encoding to enhance contrast and highlight subtle wave features. These spectrograms served as inputs to convolutional neural networks (CNNs) for classification of load conditions and detection of damage-related features. Results showed reliable recognition in both copper and PLA specimens, with CNN classification accuracies exceeding 95%. Embedded PZTs were especially effective in PLA, where signal damping and environmental sensitivity often hinder surface-mounted sensors. This work demonstrates the advantages of embedded sensing in AM structures, particularly when paired with spectrogram-based feature engineering and CNN modeling, advancing real-time SHM for aerospace, energy, and defense applications.
Hyperdiverse tropical rainforests, such as the aseasonal forests in Southeast Asia, are supported by high annual rainfall. Its canopy is dominated by the species-rich tree family of Dipterocarpaceae (Asian dipterocarps), which has both ecological (e.g., supports flora and fauna) and economical (e.g., timber production) importance. Recent ecological studies suggested that rare irregular drought events may be an environmental stress and signal for the tropical trees. We assembled the genome of a widespread but near threatened dipterocarp, Shorea leprosula, and analyzed the transcriptome sequences of ten dipterocarp species representing seven genera. Comparative genomic and molecular dating analyses suggested a whole-genome duplication close to the Cretaceous-Paleogene extinction event followed by the diversification of major dipterocarp lineages (i.e. Dipterocarpoideae). Interestingly, the retained duplicated genes were enriched for genes upregulated by no-irrigation treatment. These findings provide molecular support for the relevance of drought for tropical trees despite the lack of an annual dry season.
Viruses shape microbial communities, food web dynamics, and carbon and nutrient cycling in diverse ecosystems. However, little is known about the patterns and drivers of viral community composition, particularly in soil, precluding a predictive understanding of viral impacts on terrestrial habitats. To investigate soil viral community assembly processes, here we analyzed 43 soil viromes from a rainfall manipulation experiment in a Mediterranean grassland in California. We identified 5,315 viral populations (viral operational taxonomic units [vOTUs] with a representative sequence ≥10 kbp) and found that viral community composition exhibited a highly significant distance–decay relationship within the 200-m 2 field site. This pattern was recapitulated by the intrapopulation microheterogeneity trends of prevalent vOTUs (detected in ≥90% of the viromes), which tended to exhibit negative correlations between spatial distance and the genomic similarity of their predominant allelic variants. Although significant spatial structuring was also observed in the bacterial and archaeal communities, the signal was dampened relative to the viromes, suggesting differences in local assembly drivers for viruses and prokaryotes and/or differences in the temporal scales captured by viromes and total DNA. Despite the overwhelming spatial signal, evidence for environmental filtering was revealed in a protein-sharing network analysis, wherein a group of related vOTUs predicted to infect actinobacteria was shown to be significantly enriched in low-moisture samples distributed throughout the field. Overall, our results indicate a highly diverse, dynamic, active, and spatially structured soil virosphere capable of rapid responses to changing environmental conditions.
Bacteria possess diverse mechanisms to regulate their motility in response to environmental and physiological signals, enabling them to navigate complex habitats and adapt their behavior. Some of these mechanisms are species specific and enable cells to modulate their movement based on the ecological identity of neighboring species. Here, we introduce a model in which bacteria interact via local signals that either enhance or suppress the motility of neighboring cells depending on species type. Through large-scale simulations and a coarse-grained stochastic model, we demonstrate the emergence of a sharp transition driven by nucleation processes: increasing the density of motility-suppressing interactions drives the system from a fully mixed, motile phase to a state characterized by large, stationary bacterial clusters. Remarkably, in systems with a large number of interacting species, this transition can be triggered solely by altering the structure of the motility-regulation interaction matrix while maintaining species and interaction densities constant. In particular, we find that heterogeneous and modular interactions promote the transition more readily than homogeneous random ones. These findings add a dimension to the theory of motility-induced phase separation and contribute to the ongoing effort to understand microbial interactions, suggesting that structured, nonrandom ones may be key to reproducing commonly observed spatial patterns in microbial communities.
To establish the capability for measurement of oscillatory pressure on rotating blades, miniature fast response semiconductor strain gage pressure transducers (2mm x 0.33mm) were mounted in several configurations on thin titanium and steel compressor blades and subjected to pressure cycles from 1 to 310 kPa during static tests and spin tests. Static test conditions included 20 C to 150 C, 0 to 3000 tensile microstrain, -1000 to +1000 bending microstrain and + or - 650G vibration. The spin test conditions included 20 C to 82 C at 0 to 90,000G. Durability was excellent. Pressure transducer sensitivity changed by only a few percent over this range of environmental conditions. Noise signal due to oscillatory acceleration normal to the diaphragm was acceptable (0.33Pa/G). Noise signal due to oscillatory strain was acceptable (0.5 Pa/microstrain) when the transducer was mounted on a 0.05mm rubber pad, with a total buildup of 0.38mm on the measure surface. Back mounting or partial recessing to eliminate buildup, increased the strain effect to 1.2 Pa/microstrain. Flush mounting within the blade to eliminate buildup reduced the strain effect, but required development of a special transducer shape. This transducer was not available in time for spin tests. Unpredictable zero drift + or - 14 kPa ruled out the use of these mounting arrangements for accurate steady-state (D.C.) measurements on rotating blades. The two best configurations fully developed and spin tested were then successfully applied in the NAS3-20606 rotating fan flutter program for quantitative measurement of oscillatory pressure amplitudes.
Detector for trace chemicals senses as few as 10 to the 12th power molecules of given material on surface. Contains no moving parts, amenable to large-scale integration, and operates at room temperature. Potential applications in industrial process control and in environmental analysis. Characteristic signals indicate presence of certain chemicals.
A computer program was developed to study multiple crop production and control in controlled environment plant production systems. The program simulates crop growth and development under nominal and off-nominal environments. Time-series crop models for wheat (Triticum aestivum), soybean (Glycine max), and white potato (Solanum tuberosum) are integrated with a model-based predictive controller. The controller evaluates and compensates for effects of environmental disturbances on crop production scheduling. The crop models consist of a set of nonlinear polynomial equations, six for each crop, developed using multivariate polynomial regression (MPR). Simulated data from DSSAT crop models, previously modified for crop production in controlled environments with hydroponics under elevated atmospheric carbon dioxide concentration, were used for the MPR fitting. The model-based predictive controller adjusts light intensity, air temperature, and carbon dioxide concentration set points in response to environmental perturbations. Control signals are determined from minimization of a cost function, which is based on the weighted control effort and squared-error between the system response and desired reference signal.
Sucrose (Suc) plays a central role in plant growth and development. It is a major end product of photosynthesis and functions as a primary transport sugar and in some cases as a direct or indirect regulator of gene expression. Research during the last 2 decades has identified the pathways involved and which enzymes contribute to the control of flux. Availability of metabolites for Suc synthesis and 'demand' for products of sucrose degradation are important factors, but this review specifically focuses on the biosynthetic enzyme sucrose-phosphate synthase (SPS), and the degradative enzymes, sucrose synthase (SuSy), and the invertases. Recent progress has included the cloning of genes encoding these enzymes and the elucidation of posttranslational regulatory mechanisms. Protein phosphorylation is emerging as an important mechanism controlling SPS activity in response to various environmental and endogenous signals. In terms of Suc degradation, invertase-catalyzed hydrolysis generally has been associated with cell expansion, whereas SuSy-catalyzed metabolism has been linked with biosynthetic processes (e.g., cell wall or storage products). Recent results indicate that SuSy may be localized in multiple cellular compartments: (1) as a soluble enzyme in the cytosol (as traditionally assumed); (2) associated with the plasma membrane; and (3) associated with the actin cytoskeleton. Phosphorylation of SuSy has been shown to occur and may be one of the factors controlling localization of the enzyme. The purpose of this review is to summarize some of the recent developments relating to regulation of activity and localization of key enzymes involved in sucrose metabolism in plants.
Oxidized low-density lipoprotein (oxLDL) is known to activate a number of signal transduction pathways in endothelial cells. Among these are the c-Jun NH(2)-terminal kinase (JNK), also known as stress-activated protein kinase, and extracellular signal-regulated kinase (ERK). These mitogen-activated protein kinases (MAP kinase) determine cell survival in response to environmental stress. Interestingly, JNK signaling involves redox-sensitive mechanisms and is activated by reactive oxygen and nitrogen species derived from both NADPH oxidases, nitric oxide synthases (NOS), peroxides, and oxidized low-density lipoprotein (oxLDL). The role of endothelial NOS (eNOS) in the activation of JNK in response to oxLDL has not been examined. Herein, we show that on exposure of endothelial cells to oxLDL, both ERK and JNK are activated through independent signal transduction pathways. A key role of eNOS activation through a phosphatidylinositol-3-kinase-dependent mechanism leading to phosphorylation of eNOS is demonstrated for oxLDL-dependent activation of JNK. Moreover, we show that activation of ERK by oxLDL is critical in protection against the cytotoxicity of oxLDL.
The initial steps taken in developing a completely menu driven and totally automated computer control system for a bioreactor are discussed. This bioreactor is an electro-mechanical cell growth system cell requiring vigorous control of slowly changing parameters, many of which are so dynamically interactive that computer control is a necessity. The process computer will have two main functions. First, it will provide continuous environmental control utilizing low signal level transducers as inputs and high powered control devices such as solenoids and motors as outputs. Secondly, it will provide continuous environmental monitoring, including mass data storage and periodic data dumps to a supervisory computer.