Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “activation function”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Payload/orbiter contamination control requirement study

A study was conducted to determine and quantify the expected particulate and molecular on-orbit contaminant environment for selected space shuttle payloads as a result of major shuttle orbiter contamination sources. Individual payload susceptibilities to contamination are reviewed. The risk of payload degradation is identified and preliminary recommendations are provided concerning the limiting factors which may depend on operational activities associated with the payload/orbiter interface or upon independent payload functional activities. A basic computer model of the space shuttle orbiter which includes a representative payload configuration is developed. The major orbiter contamination sources, locations, and flux characteristics based upon available data have been defined and modeled.

Bareiss, L. E.↗
NASA NTRS2006

A Thermodynamically Consistent Damage Model for Advanced Composites

A continuum damage model for the prediction of damage onset and structural collapse of structures manufactured in fiber-reinforced plastic laminates is proposed. The principal damage mechanisms occurring in the longitudinal and transverse directions of a ply are represented by a damage tensor that is fixed in space. Crack closure under load reversal effects are taken into account using damage variables established as a function of the sign of the components of the stress tensor. Damage activation functions based on the LaRC04 failure criteria are used to predict the different damage mechanisms occurring at the ply level. The constitutive damage model is implemented in a finite element code. The objectivity of the numerical model is assured by regularizing the dissipated energy at a material point using Bazant's Crack Band Model. To verify the accuracy of the approach, analyses of coupon specimens were performed, and the numerical predictions were compared with experimental data.

Maimi, Pere↗
NASA NTRS1974

Heliobiology, its development, successes and tasks

Heliobiology studies the influence of changes in solar activity on life. Considered are the influence of periodic solar activity on the development and growth of epidemics, mortality from various diseases, the functional activity of the nervous system, the development of psychic disturbances, the details of the development of microorganisms and many other phenomena in the living world.

Platonova, A. T.↗
DOE OSTI2022

Structural characterization of a soil viral auxiliary metabolic gene product – a functional chitosanase

Metagenomics is unearthing the previously hidden world of soil viruses. Many soil viral sequences in metagenomes contain putative auxiliary metabolic genes (AMGs) that are not associated with viral replication. Here, we establish that AMGs on soil viruses actually produce functional, active proteins. We focus on AMGs that potentially encode chitosanase enzymes that metabolize chitin – a common carbon polymer. We express and functionally screen several chitosanase genes identified from environmental metagenomes. One expressed protein showing endo-chitosanase activity (V-Csn) is crystalized and structurally characterized at ultra-high resolution, thus representing the structure of a soil viral AMG product. This structure provides details about the active site, and together with structure models determined using AlphaFold, facilitates understanding of substrate specificity and enzyme mechanism. Our findings support the hypothesis that soil viruses contribute auxiliary functions to their hosts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Probe for selectively characterizing enzymes involved in xenobiotic metabolism and method of making and using the same

Activity-based probes that can be used to selectively identify and characterize enzymes that are involved in different phases of xenobiotic metabolism in a host and its microbiota population(s) are described. The activity-based probes described specifically label only their target active enzymes involved in xenobiotic metabolism and therefore provide a measurement of true protein functional activity rather than transcript or protein abundance. The activity-based probes also provide multimodal profiling of these active enzymes. Methods for preparing the activity based probes and exemplary methods for their use also are disclosed.

Wright, Aaron T.↗
DOE OSTI2024

Probe for selectively characterizing enzymes involved in xenobiotic metabolism and method of making and using the same

Activity-based probes that can be used to selectively identify and characterize enzymes that are involved in different phases of xenobiotic metabolism in a host and its microbiota population(s) are described. The activity-based probes described specifically label only their target active enzymes involved in xenobiotic metabolism and therefore provide a measurement of true protein functional activity rather than transcript or protein abundance. The activity-based probes also provide multimodal profiling of these active enzymes. Methods for preparing the activity based probes and exemplary methods for their use also are disclosed.

Wright, Aaron T.↗
DOE OSTI2023

Combinatorial optimization and spatial remodeling of CYPs to control product profile

Activating inert substrates is a challenge in nature and synthetic chemistry, but essential for creating functionally active molecules. In this work, we used a combinatorial optimization approach to assemble cytochrome P450 monooxygenases (CYPs) and reductases (CPRs) to achieve a target product profile. By creating 110 CYP-CPR pairs and iteratively screening different pairing libraries, we demonstrated a framework for establishing a CYP network that catalyzes six oxidation reactions at three different positions of a chemical scaffold. Target product titer was improved by remodeling endoplasmic reticulum (ER) size and spatially controlling the CYPs’ configuration on the ER. Out of 47 potential products that could be synthesized, 86% of the products synthesized by the optimized network was our target compound quillaic acid (QA), the aglycone backbone of many pharmaceutically important saponins, and fermentation achieved QA titer 2.23 g/L.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1974

Payload/orbiter contamination control requirement study, volume 1, exhibit A

This study is to identify and quantify the expected molecular and particulate on orbit contaminant environment for selected shuttle payloads as a result of major spacelab and shuttle orbiter contaminant sources. This investigation reviews individual payload susceptibilities to contamination, identifies the combined induced environment, identifies the risk of spacelab/payload critical surface(s) degradation, and provides preliminary contamination recommendations. It also establishes limiting factors which may depend upon operational activities associated with the payloads, spacelab, and the shuttle orbiter interface or upon independent payload functional activities.

Bareiss, L. E.↗
NASA NTRS1992

Membership generation using multilayer neural network

There has been intensive research in neural network applications to pattern recognition problems. Particularly, the back-propagation network has attracted many researchers because of its outstanding performance in pattern recognition applications. In this section, we describe a new method to generate membership functions from training data using a multilayer neural network. The basic idea behind the approach is as follows. The output values of a sigmoid activation function of a neuron bear remarkable resemblance to membership values. Therefore, we can regard the sigmoid activation values as the membership values in fuzzy set theory. Thus, in order to generate class membership values, we first train a suitable multilayer network using a training algorithm such as the back-propagation algorithm. After the training procedure converges, the resulting network can be treated as a membership generation network, where the inputs are feature values and the outputs are membership values in the different classes. This method allows fairly complex membership functions to be generated because the network is highly nonlinear in general. Also, it is to be noted that the membership functions are generated from a classification point of view. For pattern recognition applications, this is highly desirable, although the membership values may not be indicative of the degree of typicality of a feature value in a particular class.

Kim, Jaeseok↗
NASA NTRS2002

Molecular cloning and characterization of a tumor-associated, growth-related, and time-keeping hydroquinone (NADH) oxidase (tNOX) of the HeLa cell surface

NOX proteins are growth-related cell surface proteins that catalyze both hydroquinone or NADH oxidation and protein disulfide interchange and exhibit prion-like properties. The two enzymatic activities alternate to generate a regular period length of about 24 min. Here we report the expression, cloning, and characterization of a tumor-associated NADH oxidase (tNOX). The cDNA sequence of 1830 bp is located on gene Xq25-26 with an open reading frame encoding 610 amino acids. The activities of the bacterially expressed tNOX oscillate with a period length of 22 min as is characteristic of tNOX activities in situ. The activities are inhibited completely by capsaicin, which represents a defining characteristic of tNOX activity. Functional motifs identified by site-directed mutagenesis within the C-terminal portion of the tNOX protein corresponding to the processed plasma membrane-associated form include quinone (capsaicin), copper and adenine nucleotide binding domains, and two cysteines essential for catalytic activity. Four of the six cysteine to alanine replacements retained enzymatic activity, but the period lengths of the oscillations were increased. A single protein with two alternating enzymatic activities indicative of a time-keeping function is unprecedented in the biochemical literature.

NASA Discipline Cell Biology↗
DOE OSTI2025

Massively parallel and universal approximation of nonlinear functions using diffractive processors

Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak and power-intensive nature of optical nonlinearities. Overcoming this limitation without relying on nonlinear optical materials could unlock unprecedented opportunities for ultrafast and parallel optical computing systems. Here, we demonstrate that large-scale nonlinear computation can be performed using linear optics through optimized diffractive processors composed of passive phase-only surfaces. In this framework, the input variables of nonlinear functions are encoded into the phase of an optical wavefront—e.g., via a spatial light modulator (SLM)—and transformed by an optimized diffractive structure with spatially varying point-spread functions to yield output intensities that approximate a large set of unique nonlinear functions–all in parallel. We provide proof establishing that this architecture serves as a universal function approximator for an arbitrary set of bandlimited nonlinear functions, also covering wavelength-multiplexed nonlinear functions as well as multi-variate and complex-valued functions that are all-optically cascadable. Our analysis also indicates the successful approximation of typical nonlinear activation functions commonly used in neural networks, including the sigmoid, tanh, ReLU (rectified linear unit), and softplus. We numerically demonstrate the parallel computation of one million distinct nonlinear functions, accurately executed at wavelength-scale spatial density at the output of a diffractive optical processor. Furthermore, we experimentally validated this framework using in situ optical learning and approximated 35 unique nonlinear functions in a single shot using a compact setup consisting of an SLM and an image sensor. These results establish diffractive optical processors as a scalable platform for massively parallel universal nonlinear function approximation, paving the way for new capabilities in analog optical computing based on linear materials.

Rahman, Md Sadman Sakib [University of California,↗
NASA NTRS1992

Adaptability of the oxidative capacity of motoneurons

Previous studies have demonstrated that a chronic change in neuronal activation can produce a change in soma oxidative capacity, suggesting that: (i) these 2 variables are directly related in neurons and (ii) ion pumping is an important energy requiring activity of a neuron. Most of these studies, however, have focused on reduced activation levels of sensory systems. In the present study the effect of a chronic increase or decrease in motoneuronal activity on motoneuron oxidative capacity and soma size was studied. In addition, the effect of chronic axotomy was studied as an indicator of whether cytoplasmic volume may also be related to the oxidative capacity of motoneurons. A quantitative histochemical assay for succinate dehydrogenase activity was used as a measure of motoneuron oxidative capacity in experimental models in which chronic electromyography has been used to verify neuronal activity levels. Spinal transection reduced, and spinal isolation virtually eliminated lumbar motoneuron electrical activity. Functional overload of the plantaris by removal of its major synergists was used to chronically increase neural activity of the plantaris motor pool. No change in oxidative capacity or soma size resulted from either a chronic increase or decrease in neuronal activity level. These data indicate that the chronic modulation of ionic transport and neurotransmitter turnover associated with action potentials do not induce compensatory metabolic responses in the metabolic capacity of the soma of lumbar motoneurons. Soma oxidative capacity was reduced in the axotomized motoneurons, suggesting that a combination of axoplasmic transport, intracellular biosynthesis and perhaps neurotransmitter turnover represent the major energy demands on a motoneuron. While soma oxidative capacity may be closely related to neural activity in some neural systems, e.g. visual and auditory, lumbar motoneurons appear to be much less sensitive to modulations in chronic activity levels.

NASA Discipline Musculoskeletal↗
NASA NTRS2009

Initial Investigation of Operational Concept Elements for NASA's NextGen-Airportal Project Research

The NextGen-Airportal Project is organized into three research focus areas: Safe and Efficient Surface Operations, Coordinated Arrival/Departure Operations Management, and Airportal Transition and Integration Management. The content in this document was derived from an examination of constraints and problems at airports for accommodating future increases in air traffic, and from an examination of capabilities envisioned for NextGen. The concepts are organized around categories of constraints and problems and therefore do not precisely match, but generally reflect, the research focus areas. The concepts provide a framework for defining and coordinating research activities that are, and will be, conducted by the NextGen-Airportal Project. The concepts will help the research activities function as an integrated set focused on future needs for airport operations and will aid aligning the research activities with NextGen key capabilities. The concepts are presented as concept elements with more detailed sub-elements under each concept element. For each concept element, the following topics are discussed: constraints and problems being addressed, benefit descriptions, required technology and infrastructure, and an initial list of potential research topics. Concept content will be updated and more detail added as the research progresses. The concepts are focused on enhancing airportal capacity and efficiency in a timeframe 20 to 25 years in the future, which is similar to NextGen's timeframe.

Lohr, Gary↗
DOE OSTI2025

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

The optimization of functional materials is important to enhance their properties, but their complex geometries pose great challenges to optimization. Data-driven algorithms efficiently navigate such complex design spaces by learning relationships between material structures and performance metrics to discover high-performance functional materials. Surrogate-based active learning, continually improving its surrogate model by iteratively including high-quality data points, has emerged as a cost-effective data-driven approach. Furthermore, it can be coupled with quantum computing to enhance optimization processes, especially when paired with a special form of surrogate model (i.e., quadratic unconstrained binary optimization), formulated by factorization machine (FM). However, current practices often overlook the variability in design space sizes when determining the initial data size for optimization. In this work, we investigate the optimal initial data sizes required for efficient convergence across various design space sizes. By employing averaged piecewise linear regression, we identify initiation points where convergence begins, highlighting the crucial role of employing adequate initial data in achieving efficient optimization. These results contribute to the efficient optimization of functional materials by ensuring faster convergence and reducing computational costs in FM-based active learning.

active learning↗
DOE OSTI2022

CoordNet: Data Generation and Visualization Generation for Time-Varying Volumes via a Coordinate-Based Neural Network

Although deep learning has demonstrated its capability in solving diverse scientific visualization problems, it still lacks generalization power across different tasks. To address this challenge, we propose CoordNet, a single coordinate-based framework that tackles various tasks relevant to time-varying volumetric data visualization without modifying the network architecture. The core idea of our approach is to decompose diverse task inputs and outputs into a unified representation (i.e., coordinates and values) and learn a function from coordinates to their corresponding values. We achieve this goal using a residual block-based implicit neural representation architecture with periodic activation functions. We evaluate CoordNet on data generation (i.e., temporal super-resolution and spatial super-resolution) and visualization generation (i.e., view synthesis and ambient occlusion prediction) tasks using time-varying volumetric data sets of various characteristics. Here, the experimental results indicate that CoordNet achieves better quantitative and qualitative results than the state-of-the-art approaches across all the evaluated tasks. Source code and pre-trained models are available at https://github.com/stevenhan1991/CoordNet.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1972

The geography and human cultural resources working group of the EROS program

The functions, activities, and objectives of the Geography and Human-Cultural Resources Working Group of the EROS program are outlined. The Group's primary function is to coordinate remote sensing experiments of physical scientists and the needs of socioeconomic and culturally orientated planners, policy makers, administrators, and other user groups. Other functions of the Group include land use analysis, resource mapping, and development of an operational automatic information system receptive to land use and environmental data.

Gerlach, A. C.↗