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An experimental model of a mechanical spectrometer is reported that permits vibration measurements at 297 points on a mechanical device and processes this information by digital computer for automatic printout.
A system is described for automatic and semiautomatic tracking of objects on film or video tape which was developed to meet the needs of the microgravity combustion and fluid science experiments at NASA Lewis. The system consists of individual hardware parts working under computer control to achieve a high degree of automation. The most important hardware parts include 16 mm film projector, a lens system, a video camera, an S-VHS tapedeck, a frame grabber, and some storage and output devices. Both the projector and tapedeck have a computer interface enabling remote control. Tracking software was developed to control the overall operation. In the automatic mode, the main tracking program controls the projector or the tapedeck frame incrementation, grabs a frame, processes it, locates the edge of the objects being tracked, and stores the coordinates in a file. This process is performed repeatedly until the last frame is reached. Three representative applications are described. These applications represent typical uses and include tracking the propagation of a flame front, tracking the movement of a liquid-gas interface with extremely poor visibility, and characterizing a diffusion flame according to color and shape.
Program synthesis automatically derives programs from specifications of their behavior. One advantage of program synthesis, as opposed to manual coding, is that there is a direct link between the specification and the derived program. This link is, however, not very fine-grained: it can be best characterized as Program is-derived- from Specification. When the generated program needs to be understood or modified, more $ne-grained linking is useful. In this paper, we present a novel technique for automatically deriving traceability relations between parts of a specification and parts of the synthesized program. The technique is very lightweight and works -- with varying degrees of success - for any process in which one artifact is automatically derived from another. We illustrate the generality of the technique by applying it to two kinds of automatic generation: synthesis of Kalman Filter programs from speci3cations using the Aut- oFilter program synthesis system, and generation of assembly language programs from C source code using the GCC C compilel: We evaluate the effectiveness of the technique in the latter application.
SNAP is a neutron time-of-flight diffractometer at the Spallation Neutron Source operated by Oak Ridge National Laboratory. It generates large arrays of neutron detection events that encode the crystalline atomic structure of materials under study. SNAPRed is an application that makes these datasets accessible to end users by orchestrating the process of data reduction while automatically managing the variable neutron instrumentation configuration. It supports arbitrary grouping and masking of individual detector pixels and includes custom-developed data compression approaches to accommodate the large volumes of data generated by the SNAP instrument.
Global plastic waste generation exceeds 430 million tonnes per year, yet fewer than 9% are recycled in the United States. Pyrolysis offers a chemical recycling route at scale, but existing techno-economic and life cycle assessments fix product yields to single pure polymers, producing economic and environmental outputs that break down when the feed composition changes. Here, we present a superstructure optimization framework that addresses this by embedding a composition-aware random forest yield predictor, trained on 566 pyrolysis experiments, within a full-scale process simulation. Product distributions update automatically as feed allocation shifts across four reactor chemistries: conventional thermal, catalytic (HZSM-5), thermal oxo-degradation, and nonequilibrium CO2 plasma. The optimal superstructure achieves minimum selling prices of −0.56 to −0.76/kg feed and global warming potentials of −0.276 to −0.322 kg CO2-eq/kg feed across four commodity price scenarios, confirming profitable, carbon-negative operation without tipping fees. Carbon abatement costs of $\$$0.46 to $\$$1.25/kg CO2-eq are competitive with direct air capture. Sensitivity analysis shows that the catalytic-plasma split fraction is the single largest driver of both economic and climate performance, while hydrocracking allocation in the wax upgrading stage is emission-neutral across the full variable range. Mixed plastic waste streams, evaluated as composition-variable feedstocks rather than pure resins, are profitable and carbon-negative across realistic market conditions. These results give a quantitative basis for reactor selection, circular economy investment, and policy design targeting chemical recycling on a large scale.
Accurate molecular property prediction is important across all fields of chemistry. Deep neural networks (DNNs) have become increasingly popular due to their ability to train automatically, avoiding the incredibly tedious process of constructing and extending traditional property estimation schemes. However, DNNs require large amounts of training data, are challenging to interpret, require large amounts of memory to load even during inference, and have severe difficulties incorporating qualitative chemical knowledge, which are often desired for molecular property prediction tasks. Here, in this study, we present PySIDT (https://github.com/zadorlab/PySIDT), a software for training and running inference on Subgraph Isomorphic Decision Trees (SIDTs). SIDTs are graph-based decision trees made of nodes associated with molecular substructures. Inference is done by descending target molecular structures down the decision tree to nodes with matching subgraph isomorphic substructures and making predictions based on the final (most specific) nodes matched. SIDTs scale down well to dataset sizes much smaller than is feasible for DNNs. As trees of molecular substructures, SIDTs are inherently readable and easy to visualize, making them easy to analyze. They are also straightforward to extend and retrain, facilitate uncertainty estimation, and enable easy integration of expert knowledge. We demonstrate the SIDT approach discussing its application to a diverse range of molecular prediction tasks: rate coefficient estimation, diffusion coefficient estimation, thermochemistry estimation, transition state bond stretch prediction, p K a prediction, stability of molecular structures, stability of surface structures, and prediction of surface lateral interaction energetics. Additionally, we demonstrate the power of the SIDT algorithms in two direct learning curve vanilla comparisons with the popular DNN-based software Chemprop and the popular gradient boosted trees-based software XGBoost on enthalpy of formation and rate coefficient prediction tasks. In particular, in the enthalpy of formation case, vanilla PySIDT is able to outperform vanilla Chemprop and XGBoost across the full range of training/validation set sizes out to 11,560 data points.
Abstract There has been an ongoing need for information-rich databases in the mechanical-engineering domain to aid in data-driven materials science. To address the lack of suitable property databases, this study employs the latest version of the chemistry-aware natural-language-processing (NLP) toolkit, ChemDataExtractor, to automatically curate a comprehensive materials database of key stress-strain properties. The database contains information about materials and their cognate properties: ultimate tensile strength, yield strength, fracture strength, Young’s modulus, and ductility values. 720,308 data records were extracted from the scientific literature and organized into machine-readable databases formats. The extracted data have an overall precision, recall and F-score of 82.03%, 92.13% and 86.79%, respectively. The resulting database has been made publicly available, aiming to facilitate data-driven research and accelerate advancements within the mechanical-engineering domain.
The ePIC collaboration adopted the JANA2 framework to manage its reconstruction algorithms. This framework has since evolved substantially in response to ePIC’s needs. There have been three main design drivers: integrating cleanly with the Podio-based data models and other layers of the key4hep stack, enabling external configuration of existing components, and supporting timeframe splitting for streaming readout. The result is a unified component model featuring a new declarative interface for specifying inputs, outputs, parameters, services, and resources. This interface enables the user to instantiate, configure, and wire components via an external file. One critical new addition to the component model is a hierarchical decomposition of data boundaries into levels such as Run, Timeframe, PhysicsEvent, and Subevent. Two new component abstractions, Folder and Unfolder, are introduced in order to traverse this hierarchy, e.g. by splitting or merging. The pre-existing components can now operate at different event levels, and JANA2 will automatically construct the corresponding parallel processing topology. This means that a user may write an algorithm once, and configure it at runtime to operate on timeframes or on physics events. Overall, these changes mean that the user requires less knowledge about the framework internals, obtains greater flexibility with configuration, and gains the ability to reuse the existing abstractions in new streaming contexts.
Magnetic dopants in three-dimensional topological insulators (TIs) offer a promising avenue for realizing the quantum anomalous Hall effect (QAHE) without the necessity for an external magnetic field. Understanding the relationship between site occupancy of magnetic dopant elements and their effect on macroscopic property is crucial for controlling the QAHE. By combining atomic-scale energy-dispersive X-ray spectroscopy (EDS) maps obtained by aberration-corrected scanning transmission electron microscopy (AC-STEM) and novel data processing methodologies, including semi-automatic lattice averaging and frame registration, we have determined the substitutional sites of Mn atoms within the 1.2% Mn-doped Sb 2 Te 3 crystal. More importantly, the methodology developed in this study extends beyond Mn-doped Sb 2 Te 3 to other quantum materials, traditional semiconductors, and even electron irradiation sensitive materials.
The Third Wind Forecast Improvement Project (WFIP3) is a multi-institutional field campaign designed to advance the understanding and prediction of the offshore atmospheric boundary layer along the US east coast. Extending from February 2024 through August 2025, WFIP3 combines long-term coastal and offshore measurements with targeted modeling and forecasting efforts. This data paper presents the WFIP3 event log, a curated record of 578 d of meteorological phenomena and field observations that complements the campaign's extensive high-frequency datasets. The event log provides both manually documented daily weather discussions and automatically derived indicators of atmospheric processes – including low-level jets, wind ramps, extreme wind veer, and weak wind conditions – based on observations from scanning lidars deployed at three coastal and offshore sites. The dataset offers structured metadata, standardized time and site identifiers, and consistent terminology to facilitate its integration with WFIP3's observational and modeling data products. The log supports diverse applications, from model evaluation and forecast verification to the selection of case studies on offshore boundary-layer dynamics. The WFIP3 event log is publicly available through the US Department of Energy's Wind Data Hub, providing the research community with a transparent and enduring contextual reference for the interpretation and use of WFIP3 measurements.
Frequency shifting, commonly used in electronic signal processing, is applied in tuning, automatic frequency control, antenna element switching, phase shifting, etc. Frequency shifting can be accomplished economically and reliably with simple circuit comprising conventional resistor and solid-state switching device which can be equivalent to two capacitors, depending on switching state.
The DSN telemetry system now includes the capability to provide a complete magnetic tape record, within 24 hours of reception, of all telemetry data received from a spacecraft. This record, the intermediate data record, is processed and generated almost entirely automatically, and provides a detailed accounting of any missing data.
The TDRSS will provide telecommunications support to near-earth orbiting satellites through the 1980s and into the 1990s. The system incorporates two operational satellites at geostationary altitude and a single ground station at White Sands, NM. Of the many tasks facing the engineering team in development of this system, one of the most challenging was K-band autotrack. An approach not previously attempted placed the error detection, processing, and feedback elements for automatic control of the TDR satellite antennas on the ground. This approach offered several advantages to the designers but posed a number of interesting questions during the development program. The autotrack system design and its test program are described with emphasis given to areas of special interest in developing a working K-band service.
The thrust of the present work is to explore the utility of using a sum of sinusoids (seven or more) to obtain an evoked response and, furthermore, to see if the response is sensitive to changes in cognitive processing. Within the field of automatic control system technology, a mathematical input/output relationship for a sinusoidally stimulated nonlinear system is defined as describing function. Applying this technology, sum of sines inputs to yield describing functions for the visual-cortical response have been designed. What follows is a description of the method used to obtain visual-cortical describing functions. A number of measurement system redesigns were necessary to achieve the desired frequency resolution. Results that guided and came out of the redesigns are presented. Preliminary results of stimulus parameter effects (average intensity and depth of modulation) are also shown.
An image processing system was developed which automatically analyzes the size distributions in fuel spray video images. Images are generated by using pulsed laser light to freeze droplet motion in the spray sample volume under study. This coherent illumination source produces images which contain droplet diffraction patterns representing the droplets degree of focus. The analysis is performed by extracting feature data describing droplet diffraction patterns in the images. This allows the system to select droplets from image anomalies and measure only those droplets considered in focus. Unique features of the system are the totally automated analysis and droplet feature measurement from the grayscale image. The feature extraction and image restoration algorithms used in the system are described. Preliminary performance data is also given for two experiments. One experiment gives a comparison between a synthesized distribution measured manually and automatically. The second experiment compares a real spray distribution measured using current methods against the automatic system.
The National Aeronautics and Space Administration's Jet Propulsion Laboratory (JPL) and the U.S. Department of Agriculture (USDA) Forest Service completed a conceptual design study that defined an integrated forest fire detection and mapping system that will be based upon technology available in the 1990s. Potential system configuration options in emerging and advanced technologies related to the conceptual design were identified and recommended for inclusion as preferred system components. System component technologies identified for an end-to-end system include airborne mounted, thermal infrared (IR) linear array detectors, automatic onboard georeferencing and signal processing, geosynchronous satellite communications links, and advanced data integration and display. Potential system configuration options were developed and examined for possible inclusion in the preferred system configuration. The preferred system configuration will provide increased performance and be cost effective over the system currently in use. Forest fire management user requirements and the system component emerging technologies were the basis for the system configuration design. The conceptual design study defined the preferred system configuration that warrants continued refinement and development, examined economic aspects of the current and preferred system, and provided preliminary cost estimates for follow-on system prototype development.
The 'Firefly' project is developing an infrared remote sensing system to provide near real-time wildland fire information for fire management and suppression. Recent technological advances in several areas now allow the design of an end-to-end, infrared system to map and detect wildland fires. The system components will include an airborne infrared sensor, automatic onboard signal and data processing, telecommunications link, and integration into a ground data terminal. The system will provide improved performance over current systems in terms of increased timeliness of data delivery, quantifiable accuracy, data consistency, reliability, and maintainability. The system will be the next generation of wildland fire mapping and detection system for the United States Forest Service.
First phase development of an advanced modulation technology which synergistically combines coding and modulation to achieve 2 bits per second per Hertz bandwidth efficiency in satellite demodulators is nearing completion. A proof-of-concept model is being developed to demonstrate technology feasibility, establish practical bandwidth efficiency limitations, and provide a data base for the design and development of engineering model satellite demodulators. The basic considerations leading to the choice of 4 x 4 quadrature amplitude modulation (16-QAM) and its associated coding format are discussed, along with the basic implementation of the carrier and clock recovery, automatic gain control, and decoding process. Preliminary performance results are presented. Spectra for the modulated signal shows the effects of the square root Nyquist filters in the modulation. Bit error rate (BER) results for the encoder/decoder subsystem show near ideal results, although power consumption is high and baseband BER performance of the Nyquist filter set is poor. Recommendations regarding the present system to improve BER performance and acquisition speed are given.