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At least 1,639 records · Page 91

Application of LANDSAT digital data for monitoring drought

A technique utilizing transformed LANDSAT digital data for detection of agricultural vegetative water stress was developed during the 1976 South Dakota drought, and expanded to the U.S. Great Plains the following year to evaluate its effectiveness in detecting and monitoring vegetative stress water stress over large areas. This technique, the green index number (GIN), indicated when the vegetation within a segment was undergoing stress. Segments were classified as either moisture-stressed or normal using remote sensing techniques combined with a knowledge of crop condition. The remote sensing-based information was compared to a weekly ground-based index (the crop moisture index) provided by the U.S. Dept. of Commerce. The approaches used and the results from the GIN monitoring program are presented.

Thompson, D. R.↗

Molecular Recognition at Mineral Interfaces: Implications for the Beneficiation of Rare Earth Ores

Ce-bastnäsite is the single largest mineral source for light rare-earth elements. In view of the growing industrial importance of rare-earth minerals, it is critical to develop more efficient methods for separating the valuable rare-earth-containing minerals from the surrounding gangue. In this work, we employ a combination of periodic density functional theory (DFT) and molecular mechanics (MM) calculations together with the de novo molecular design program HostDesigner to identify bis-phosphinate ligands that preferentially bind to the (100) Ce-bastnäsite surface rather than the (104) calcite surface. DFT calculations for a simple phosphinate ligand were employed to qualitatively understand key behaviors involved in ligand–metal, ligand–solvent, and solvent–metal interactions. These insights were then used to guide the search for flexible, rigid, and semirigid hydrocarbon linkers to identify candidate bis-phosphinate ligands with the potential to bind preferentially to Ce-bastnäsite. Among the five most promising bis-phosphinate ligands suggested by theoretical studies, three ligands were synthesized and their adsorption characteristics to bastnäsite (100) interfaces were characterized using vibrational sum-frequency (vSFG) spectroscopy, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, and isothermal titration calorimetry (ITC). The efficacy of the selective interfacial molecular binding was demonstrated by identifying a bis-phosphinate ligand capable of providing an overall higher surface coverage of alkyl groups relative to a monophosphinate ligand. The results highlight the interplay between adsorption binding strength and maximum surface coverage in determining ligand efficiency to render the mineral surface hydrophobic. DFT calculations further indicate that all tested ligands have higher affinity for Ce-bastnäsite than for calcite. Finally, this is consistent with the ITC data showing stronger adsorption enthalpy to bastnäsite than to calcite, making these ligands promising candidates for selective flotation of Ce-bastnäsite.

58 GEOSCIENCES↗

Differentiable vertex fitting for jet flavor tagging

This work explores the use of differentiable programming to integrate domain knowledge, in the form of domain specific software, into neural networks to develop scientific machine learning systems. We propose a differentiable vertex fitting algorithm that estimates the crossing point of multiple curves. In the high energy physics setting, these curves are defined by particle equations of motion and the crossing point represents the origin of particle production. This differentiable vertex fitting algorithm can be seamlessly integrated into neural networks, and we show its utility and efficacy in the high energy physics application of the classification of jets, i.e., collimated streams of particles in particle detectors whose originating parent particle we aim to classify. We demonstrate how differentiable vertex fitting can be integrated into larger transformer-based models for jet flavor tagging and show improvements in heavy flavor jet classification when compared to baseline models. Published by the American Physical Society 2024

Smith, Rachel E. C. (ORCID:0000000335851262)↗

AI Applications to Physics Experiments at Jefferson Lab

We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.

Mei, Xinxin [Thomas Jefferson National Accelerator↗

Time-temperature behavior of a unidirectional graphite/epoxy composite

A testing program to determine the time-temperature response of unidirectional T300/934 graphite/epoxy materials is presented. The short-term creep test results of tension specimens with the load at various angles to the fiber direction and at various temperatures are reported, showing that the material is elastic at all temperatures when the fiber is in the load direction. However, when the load is transverse to the fibers, the viscoelastic response varies from small amounts at room temperature to large amounts at temperatures above the 180 C transition temperature. The time-temperature superposition principle or the method of reduced variables were used to determine compliance master curves for each fiber angle, and a viscoelastic analog to the elastic orthotropic transformation equation was used incrementally to predict the master curves for the tensile compliance of the off-axis specimen.

Yeow, Y. T.↗

Automatic discovery of optimal classes

A criterion, based on Bayes' theorem, is described that defines the optimal set of classes (a classification) for a given set of examples. This criterion is transformed into an equivalent minimum message length criterion with an intuitive information interpretation. This criterion does not require that the number of classes be specified in advance, this is determined by the data. The minimum message length criterion includes the message length required to describe the classes, so there is a built in bias against adding new classes unless they lead to a reduction in the message length required to describe the data. Unfortunately, the search space of possible classifications is too large to search exhaustively, so heuristic search methods, such as simulated annealing, are applied. Tutored learning and probabilistic prediction in particular cases are an important indirect result of optimal class discovery. Extensions to the basic class induction program include the ability to combine category and real value data, hierarchical classes, independent classifications and deciding for each class which attributes are relevant.

Cheeseman, Peter↗

The role of time and speed in NASA's SUNLITE program

The SUNLITE program of NASA's LaRC aims to demonstrate lower noise and better frequency stability for continuous-wave (CW) solid-state lasers in the microgravity environment of space. The program will utilize laser-diode-pumped nonplanar-ring oscillators regulated by ultra-stable high-finesse Fabry-Perot Spectrometers to produce light beams with phase rate or frequency variations as low as 3 Hz. SUNLITE will use the period-method (P-method) to measure the phase rate and frequency stability of the lasers. The P-method was chosen because it requires less memory space for the raw data, because frequencies can be analyzed on-line in real-time simply by reciprocating the periods (fi = 1/pi), and because the mean and variance of the frequencies can be calculated as fast or faster than they can be with the fastest fast Fourier transformations. Furthermore, for a given signal-to-noise power ratio, the P-method requires less data and less computer time to extract the noise components. Although the P-method does require fast Time Interval Counters, the Fourier transformation method requires comparably fast Sampling Volt meters. For either method, however, time and computer speed play a critical role.

Hafele, Joseph C.↗

Spatial Resolution Characterization for AWiFS Multispectral Images

Within the framework of the Joint Agency Commercial Imagery Evaluation program, the National Aeronautics and Space Administration, the National Geospatial-Intelligence Agency, and the U.S. Geological Survey cooperate in the characterization of high-to-moderate-resolution commercial imagery of mutual interest. One of the systems involved in this effort is the Advanced Wide Field Sensor (AWiFS) onboard the Indian Remote Sensing (IRS) Reourcesat-1 satellite, IRS-P6. Spatial resolution of the AWiFS multispectral images was characterized by estimating the value of the system Modulation Transfer Function (MTF) at the Nyquist spatial frequency. The Nyquist frequency is defined as half the sampling frequency, and the sampling frequency is equal to the inverse of the ground sample distance. The MTF was calculated as a ratio of the Fourier transform of a profile across an AWiFS image of the Lake Pontchartrain Causeway Bridge and the Fourier transform of a profile across an idealized model of the bridge for each spectral band evaluated. The mean MTF value for the AWiFS imagery evaluated was estimated to be 0.1.

Blonski, Slawomir↗

In-vivo Raman microspectroscopy reveals differential nitrate concentration in different developmental zones in Arabidopsis roots

Abstract Background Nitrate (NO 3 − ) is one of the two major forms of inorganic nitrogen absorbed by plant roots, and the tissue nitrate concentration in roots is considered important for optimizing developmental programs. Technologies to quantify the expression levels of nitrate transporters and assimilating enzymes at the cellular level have improved drastically in the past decade. However, a technological gap remains for detecting nitrate at a high spatial resolution. Using extraction-based methods, it is challenging to reliably estimate nitrate concentration from a small volume of cells (i.e., with high spatial resolution), since targeting a small or specific group of cells is physically difficult. Alternatively, nitrate detection with microelectrodes offers subcellular resolution with high cell specificity, but this method has some limitations on cell accessibility and detection speed. Finally, optical nitrate biosensors have very good ( in-vivo ) sensitivity (below 1 mM) and cellular-level spatial resolution, but require plant transformation, limiting their applicability. In this work, we apply Raman microspectroscopy for high-dynamic range in-vivo mapping of nitrate in different developmental zones of Arabidopsis thaliana roots in-situ . Results As a proof of concept, we have used Raman microspectroscopy for in-vivo mapping of nitrate content in roots of Arabidopsis seedlings grown on agar media with different nitrate concentrations. Our results revealed that the root nitrate concentration increases gradually from the meristematic zone (~ 250 µm from the root cap) to the maturation zone (~ 3 mm from the root cap) in roots grown under typical growth conditions used for Arabidopsis, a trend that has not been previously reported. This trend was observed for plants grown in agar media with different nitrate concentrations (0.5–10 mM). These results were validated through destructive measurement of nitrate concentration. Conclusions We present a methodology based on Raman microspectroscopy for in-vivo label-free mapping of nitrate within small root tissue volumes in Arabidopsis. Measurements are done in-situ without additional sample preparation. Our measurements revealed nitrate concentration changes from lower to higher concentration from tip to mature root tissue. Accumulation of nitrate in the maturation zone tissue shows a saturation behavior. The presented Raman-based approach allows for in-situ non-destructive measurements of Raman-active compounds.

Fernández González, Alma↗

A Machine-Learning Approach to Assess Aircraft Engine System Performance

Artificial intelligence (AI)/machine learning, and big data are transforming the global business environment. They have become the most disruptive technologies for organizations to improve workplace efficiency and productivity. This work explored the application of machine learning-based predictive analytics that would enable aircraft engine designers to estimate engine system performance quickly during the conceptual design stage. Supervised machine-learning algorithm was employed to study patterns in an existing database of production and research turbofan engines, and built predictive analytics for use in predicting system performance of new turbofan designs. Specifically, the author developed deep-learning analytics to predict turbofan system weight, using turbofan design parameters as the input. The predictive analytics were trained and deployed in Keras, an open-source neural networks API (application program interface) written in Python, with TensorFlow (an open-source artificial AI library developed by Google) serving as the backend engine. The current engine-weight prediction results, together with those for the TSFC (thrust specific fuel consumption) and core-size predictions that were studied previously by the author, show that machine learning-based predictive analytics can be an effective, time-saving tool for aircraft engine design-space exploration during the conceptual design stage. It would enable expeditious identification of the best engine design amongst several candidates.

Michael T Tong↗

NASA GeneLab: Open Science for Life in Space

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics data and collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 350 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab Sequencing Lab. The GLDS contains rich metadata about each experiment and has integrated radiation dosimetry data from experiments flown on the Space Shuttle, International Space Station, and Free Flying spacecrafts. With the increasing amount and complexity of omics data being generated, GeneLab utilizes community-defined, common models for metadata and terminology so that omics data and results are discoverable and reliably reproducible. GeneLab uses the ISA-Tab specification and semantic model for organizing and representing omics metadata. In addition to metadata standards, data files must be open-source file or common exchange formats to ensure accessibility and usability by all users. To ease data ingestion and transfer, the web-based submission tool allows PIs a user-friendly user interface to curate, organize, and publish their space relevant omics data. In the more recent years, data curation and submission portal has incorporated the FAIR principles making data findable, accessible, interoperable, and reusable. To increase reusability of data, GeneLab has implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretation of the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 200 scientists from NASA, industry, and academia. To explore the data, the GLDS provides users various tools for data analysis, collaborative workspace for file storage and sharing, and a visualization portal. The analysis platform built using the Galaxy toolshed provides access to a broad variety of users including those with limited bioinformatics experience and students to learn how to analyze spaceflight omics data. The visualization portal takes GeneLab one step closer to data democratization by removing all bioinformatics requisites to interpret transcriptomics data hosted in the repository. To train the next generation of scientists, NASA offers training programs such as GeneLab 4 High School (GL4HS) and GeneLab 4 Universities. NLM Curation at a Scale Workshop 2022 | NASA GeneLab (GL4U) to teach students bioinformatics and computational biology methods to analyze omics data. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight.

GeneLab↗

Integrated Component-Specific Measurements to Develop Emission Factors for Compressors and Gas Gathering Lines

The Department of Energy (DOE) National Energy Technology Laboratory (NETL) and other critical stakeholders (e.g., U.S. Environmental Protection Agency (USEPA), state regulators, and industry) seek to more accurately characterize and quantify methane emissions from compressors and gathering lines within the Gathering and Boosting (G&B) segment of the natural gas system network. These efforts will reduce uncertainties in emissions estimates in USEPA’s current Green House Gas Inventory (GHGI) under their Greenhouse Gas Reporting Program (GHGRP). For this study, four G&B stations in the Gulf Coast Area were visited four times over the course of one year. Components were classified according to equipment and component type and emissions from select components were measured using multiple measurement technologies. The following major equipment types were considered: i) compressors, ii) separators, iii) dehydrators, iv) coalescers, v) slug catchers, vi) yard piping, vii) tanks, and viii) gathering lines. Individual components on each equipment type were further divided into the following main categories: i) connectors, ii) valves, iii) pressure relief valves (PRV), iv) meters, v) gauges, vi) regulators, vii) pneumatic device vents, and viii) compressor vents (e.g., distance piece vents [DPVs] and rod packing vents [RPVs]). Components were screened for the presence of leaks and venting emissions with an optical gas imaging (OGI) camera, and methane emission rates were measured using a microdilution high volume sampler. Downwind emissions were measured using an Open Path Fourier Transform Infrared (OP-FTIR) Spectrometer. Data were evaluated to assess correlation with site, equipment, time, and operational variables. Key findings and recommendations from the study include: A) Different counting methodologies can result in vastly different component counts, thus influencing total emissions calculations using Subpart W population EFs. A standard methodology should be adopted for classifying and counting components in order to minimize inconsistencies across studies and instruct stakeholders responsible for GHGI reporting. B) Results support current component subcategories listed in USEPA Subpart W, including the subdivision of connectors (flanged and “other”) and pneumatic device vents (intermittent, continuous low bleed, and continuous high bleed). C) Emission rates vary across sites and a relationship between higher emissions and compressor age was observed for some components. D) Component emission rates varied between field campaigns. The type of components contributing to overall measured emissions also varied among field campaigns. However, the emission rate variability was larger between different components (of the same category) than the variability in one component over the four field campaigns. Therefore, when calculating emission factors, it is not necessary to take repeat measurements to capture component variability. E) Measuring the emission rate of a sample for an extended period of time is not necessary to capture the average component emission rate. F) For reporting purposes, excluding liquid lines from site-wide screening may have a negligible effect on component-related emissions. However, from a site management perspective, malfunctioning components were not uncommon on liquid lines and contributed substantially to fugitive emissions at some sites. G) Population EFs, whether including or excluding liquid lines, were a conservative estimate of fugitive emissions. Leaker EFs consistently underestimated emissions at the field sites. Measurements at more sites, particularity sites in other areas of the country, need to be completed before determining the accuracy of EFs.

03 NATURAL GAS↗

Functional composites by programming entropy-driven nanosheet growth

Here, nanomaterials must be systematically designed to be technologically viable. Driven by optimizing intermolecular interactions, current designs are too rigid to plug in new chemical functionalities and cannot mitigate condition differences during integration. Despite extensive optimization of building blocks and treatments, accessing nanostructures with the required feature sizes and chemistries is difficult. Programming their growth across the nano-to-macro hierarchy also remains challenging, if not impossible. To address these limitations, we should shift to entropy-driven assemblies to gain design flexibility, as seen in high-entropy alloys, and program nanomaterial growth to kinetically match target feature sizes to the mobility of the system during processing. In tis report, following a micro-then-nano growth sequence in ternary composite blends composed of block-copolymer-based supramolecules, small molecules and nanoparticles, we successfully fabricate high-performance barrier materials composed of more than 200 stacked nanosheets (125 nm sheet thickness) with a defect density less than 0.056 µm -2 and about 98% efficiency in controlling the defect type. Contrary to common perception, polymer-chain entanglements are advantageous to realize long-range order, accelerate the fabrication process (<30 min) and satisfy specific requirements to advance multilayered film technology. This study showcases the feasibility, necessity and unlimited opportunities to transform laboratory nanoscience into nanotechnology through systems engineering of self-assembly.

42 ENGINEERING↗

Automatic Focus Adjustment of a Microscope

AUTOFOCUS is a computer program for use in a control system that automatically adjusts the position of an instrument arm that carries a microscope equipped with an electronic camera. In the original intended application of AUTOFOCUS, the imaging microscope would be carried by an exploratory robotic vehicle on a remote planet, but AUTOFOCUS could also be adapted to similar applications on Earth. Initially control software other than AUTOFOCUS brings the microscope to a position above a target to be imaged. Then the instrument arm is moved to lower the microscope toward the target: nominally, the target is approached from a starting distance of 3 cm in 10 steps of 3 mm each. After each step, the image in the camera is subjected to a wavelet transform, which is used to evaluate the texture in the image at multiple scales to determine whether and by how much the microscope is approaching focus. A focus measure is derived from the transform and used to guide the arm to bring the microscope to the focal height. When the analysis reveals that the microscope is in focus, image data are recorded and transmitted.

Huntsberger, Terrance↗

Generating Solid Models from Topographical Data

A method of generating solid models of terrain involves the conversion of topographical data into a form useable by a rapid-prototyping (RP) machine. The method was developed to enable the use of the RP machine to make solid models of Martian terrain from Mars Orbiter laser-altimeter topographical data. The method is equally applicable to the generation of models of the terrains of other astronomical bodies, including other planets, asteroids, and Earth. Topographical data describe a terrain in terms of a set of three-dimensional coordinates [e.g., Cartesian (x,y,z) or polar (latitude, longitude, radius) coordinates] of points or nodes on the terrain surface. The input data for the RP machines are required to provide a three-dimensional description, not of a single surface, but of a volume in this case, a ground volume that underlies the terrain surface. The description is required to be in the form of triangular elements that connect the nodes of all the surfaces and that completely bound the volume, with no open areas, no overlap of triangles, and no extraneous geometric elements. The software used in the present model-generation method was written in IDL - an advanced programming language that affords a number of tools, including subroutines that triangularize surfaces. The software creates a volume from the topographical surface data by adding sides to the edges of the terrain surface and joining the sides with a bottom surface. Each of the sides is triangularized by use of IDL subroutines, and then the software searches for extraneous elements and removes them. Topographical data are usually presented in a grid corresponding to polar coordinates, so that a model generated from such data is equivalent to a topographical map in Mercator projection. However an RP machine is fully capable of including the curvature of a planetary body in a model that it makes. Therefore, the software also offers a capability to transform the topographical data to a projection onto a surface having a curvature corresponding to that of the surface of the modeled planet.

Keller, John W.↗

Space station electrical power distribution analysis using a load flow approach

The space station's electrical power system will evolve and grow in a manner much similar to the present terrestrial electrical power system utilities. The initial baseline reference configuration will contain more than 50 nodes or busses, inverters, transformers, overcurrent protection devices, distribution lines, solar arrays, and/or solar dynamic power generating sources. The system is designed to manage and distribute 75 KW of power single phase or three phase at 20 KHz, and grow to a level of 300 KW steady state, and must be capable of operating at a peak of 450 KW for 5 to 10 min. In order to plan far into the future and keep pace with load growth, a load flow power system analysis approach must be developed and utilized. This method is a well known energy assessment and management tool that is widely used throughout the Electrical Power Utility Industry. The results of a comprehensive evaluation and assessment of an Electrical Distribution System Analysis Program (EDSA) is discussed. Its potential use as an analysis and design tool for the 20 KHz space station electrical power system is addressed.

Emanuel, Ervin M.↗

The Road to Mach 10: A History of the X-43A Hypersonic Flight Test Program at NASA Dryden...Toward the Future

In terms of technology, the X-43A/Hyper-X represented a singular milestone. After nearly a half century of high hopes, studies, wind tunnel tests, proposals, and canceled projects, a scramjet-powered vehicle had flown. The performance of the engine qualified the scramjet design tools and scaling laws. In turn, the theoretical calculations and ground testing could be used to design more advanced engine concepts. Just as important, both the scramjet and vehicle systems had successfully operated in the variable temperatures and densities of the atmosphere. The X-43A systems were able to maintain the exact flight conditions necessary for the scramjet to operate properly. Control deflections to correct the engine-induced moments were close to pre-flight predictions. When the unexpected occurred, such as when the vehicle pitched up during the cowl opening on the second flight, the control system was sufficiently designed to correct the situation. The airframe and wing structure, the thermal protection material, and the internal conditions of the X-43A performed largely as predicted. The HXLV thermal anomaly during the ascent on the third flight and "the Mach 8 unpleasantness" during the descent indicated that the HXLV and X-43A were not as resilient to aerodynamic heating as expected. The X-43A 's airframe drag and lift both were slightly higher than predicted, but still within preflight uncertainty predictions. The stability and control were as predicted, as was the boundary layer transition. The biggest aerodynamic worry before the flight was the separation of the HXLV and the X- 43A. After all was said and done, this went exactly as predicted, proving that non-symmetrical/high-dynamic pressure stage separations could be performed. This in turn meant that two-stage-to-orbit vehicles employing this technology were feasible. The Hyper-X program also served as a training ground for a new generation of scramjet and hypersonic researchers. This included both NASA and contractor personnel, providing them with experience in ground testing and component development; vehicle design, construction, integration, system checkout, and, ultimately, flight testing and data analysis. Additionally, researchers learned the practical details of running a project within finite budget and time limits, about the ambiguousness of risk assessment, and about the need to spend a significant amount of time and effort dealing with engineering problems, such as those with the FAS, that have nothing to do with the project's research goals. Finally, all those who worked on the X-43A project now know what it is like to spend years transforming an idea into a functional vehicle, only for it to be lost in a matter of seconds. And then to go through years of work to correct the problems, to face the possibility that still more might exist, and finally to savor the triumph of two successful flights. For those who will work on the hypersonic projects that emerge in coming years, these experiences may prove to be the most valuable of all.

Peebles, Curtis↗

An Orbital Trap Mass Analyzer Using a Hybrid Magnetic-Electric Field: A Simulation Study

An orbital ion trap mass analyzer employing hybrid magnetic-electric field was designed and simulated. The trap has a rotational symmetrical structure and the hybrid trapping field was created in a toroidal space between 12 pairs of sector detection electrodes. Ion injection and ion orbital motion inside the trap were simulated using SIMION 8.1 with a user Lua program, and the required electric and magnetic field were investigated. The image charge signal can be picked up by the 12 pairs of detection electrodes and the mass resolution was evaluated using FFT. The simulated resolving power for the optimized configuration over 79,000 FWHM was obtained at the magnetic induction intensity of 0.5 Tesla in the simulation. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗