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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.

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At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Data Management at the Advanced Photon Source

Data are crucial to the scientific discoveries enabled by experiments performed at the APS. Presently the APS generates approximately 10 PB of raw experimental data per year from its sixty-six operating beamlines that house over 100 unique instruments. This data is generated as a part of over 6,000 annual experiments performed by over 5,500 facility users each year. Similar to other synchrotrons, the amount of data generated at the APS continues to quickly increase due to beamline advances, such as new measurement techniques, technological advances in detectors, high-throughput instrumentation, multi-modal instruments that can acquire several measurements in a single experiment, and advanced data processing algorithms. This trend is expected to continue in the future. The revolutionized high-energy synchrotron facility proposed in the APS-U project will increase brightness and coherence, leading to further increases in data rates. Successful management of data is of vital importance to the current and future scientific productivity of the APS.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

RectifHydPlus Data Pipeline

The RectifHydPlus Data Pipeline is an open source and fully reproducible data processing pipeline for creating RectifHydPlus—a dataset of historical monthly net electricity generation for all US hydropower plants (>10MW). The pipeline is coded in R, applying tidyverse libraries and code principles, and using the targets data pipeline framework. All data inputs to the RectifHydPlus Data Pipeline are available from public sources. References to all data inputs, as well as instructions for running the RectifHydPlus Data Pipeline, are available on the GitLab code repository: https://code.ornl.gov/turnersw/rectifhydplus

Turner, SeanWilliam Donald [Oak Ridge National Lab↗
DOE OSTI2025

RectifHydPlus Data Pipeline v1.1.0

The RectifHydPlus Data Pipeline is an open source and fully reproducible data processing pipeline for creating RectifHydPlus—a dataset of historical monthly net electricity generation for all US hydropower plants (>10MW). The pipeline is coded in R, applying tidyverse libraries and code principles, and using the targets data pipeline framework. All data inputs to the RectifHydPlus Data Pipeline are available from public sources. References to all data inputs, as well as instructions for running the RectifHydPlus Data Pipeline, are available on the GitLab code repository: https://code.ornl.gov/turnersw/rectifhydplus

Turner, SeanWilliam Donald [Oak Ridge National Lab↗
DOE OSTI2021

MIGHTEE: total intensity radio continuum imaging and the COSMOS/XMM-LSS Early Science fields

ABSTRACT MIGHTEE is a galaxy evolution survey using simultaneous radio continuum, spectropolarimetry, and spectral line observations from the South African MeerKAT telescope. When complete, the survey will image ∼20 deg2 over the COSMOS, E-CDFS, ELAIS-S1, and XMM-Newton Large Scale Structure field (XMM-LSS) extragalactic deep fields with a central frequency of 1284 MHz. These were selected based on the extensive multiwavelength data sets from numerous existing and forthcoming observational campaigns. Here, we describe and validate the data processing strategy for the total intensity continuum aspect of MIGHTEE, using a single deep pointing in COSMOS (1.6 deg2) and a three-pointing mosaic in XMM-LSS (3.5 deg2). The processing includes the correction of direction-dependent effects, and results in thermal noise levels below 2 $\mathrm{\mu }$Jy beam−1 in both fields, limited in the central regions by classical confusion at ∼8 arcsec angular resolution, and meeting the survey specifications. We also produce images at ∼5 arcsec resolution that are ∼3 times shallower. The resulting image products form the basis of the Early Science continuum data release for MIGHTEE. From these images we extract catalogues containing 9896 and 20 274 radio components in COSMOS and XMM-LSS, respectively. We also process a close-packed mosaic of 14 additional pointings in COSMOS and use these in conjunction with the Early Science pointing to investigate methods for primary beam correction of broad-band radio images, an analysis that is of relevance to all full-band MeerKAT continuum observations, and wide-field interferometric imaging in general. A public release of the MIGHTEE Early Science continuum data products accompanies this article.

Heywood, I. (ORCID:0000000168645057)↗
DOE OSTI2018

Auto-generated materials database of Curie and Néel temperatures via semi-supervised relationship extraction

article presents an auto-generated database of 39,822 records containing chemical compounds and their associated Curie and Néel magnetic phase transition temperatures. The database was produced using natural language processing and semi-supervised quaternary relationship extraction, applied to a corpus of 68,078 chemistry and physics articles. Evaluation of the database shows an estimated overall precision of 73%. Therein, records processed with the text-mining toolkit, ChemDataExtractor, were assisted by a modified Snowball algorithm, whose original binary relationship extraction capabilities were extended to quaternary relationship extraction. Consequently, its machine learning component can now train with ≤500 seeds, rather than the 4,000 originally used. Data processed with the modified Snowball algorithm affords 82% precision. Database records are available in MongoDB, CSV and JSON formats which can easily be read using Python, R, Java and MatLab. As a result, this makes the database easy to query for tackling big-data materials science initiatives and provides a basis for magnetic materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2021

OpenMC

OpenMC is an open source, community-developed framework for performing Monte Carlo particle transport calculations.It is capable of simulating neutron and photon transport below ~50 MeV and also includes a model for bremsstrahlung production of photons by electrons/positrons. Fixed source, k-eigenvalue, and subcritical multiplication problems can be solved. Problem geometries can be modeled either using constructive solid geometry or a CAD representation. A flexible and efficient tally system enables a wide variety of physical quantities to be tallied and analyzed. OpenMC can run in parallel using a hybrid MPI and OpenMP programming model and has been extensively tested on leadership class supercomputers. A built-in Bateman equation solver enables the modeling of material composition changes due to irradiation. One of the unique features of OpenMC is its rich, extensible Python and C/C++ programming interfaces that enable programming pre- and post-processing, multigroup cross section generation, workflow automation, multiphysics coupling, and the visualization of geometry and tally results. In addition to the core Monte Carlo transport solver and associated APIs, OpenMC includes a Python-based nuclear data interface that enables power users to inspect, modify,and perform various types of nuclear data processing on ENDF, ACE, and OpenMC¿s native HDF5 files

ROMANO, PaulK.↗
DOE OSTI2015

Atomic memory access hardware implementations

Atomic memory access requests are handled using a variety of systems and methods. According to one example method, a data-processing circuit having an address-request generator that issues requests to a common memory implements a method of processing the requests using a memory-access intervention circuit coupled between the generator and the common memory. The method identifies a current atomic-memory access request from a plurality of memory access requests. A data set is stored that corresponds to the current atomic-memory access request in a data storage circuit within the intervention circuit. It is determined whether the current atomic-memory access request corresponds to at least one previously-stored atomic-memory access request. In response to determining correspondence, the current request is implemented by retrieving data from the common memory. The data is modified in response to the current request and at least one other access request in the memory-access intervention circuit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Decadal Vision Progress Report Implementation Plans and Status for the Next Generation ARM Facility

The reconfiguration of the ARM facility, formally initiated in early 2014, is geared toward implementing the Next Generation of the ARM Facility, which will more tightly link ARM measurements and atmospheric models. The strategy is outlined in the ARM Climate Research Facility Decadal Vision (DOE 2014a). The strategy includes the implementation of a high-resolution model, initially at the Southern Great Plains (SGP) site, and enhancements at the SGP and North Slope of Alaska (NSA) sites to provide additional observations to support modeling and process studies. Enhancements at the SGP site focus on ground-based instruments while enhancements at the NSA make use of Unmanned Aerial Systems (UAS) and Tethered Balloon Systems (TBS). It is also recognized that new data tools and data products will need to be developed to take full advantage of these improvements. This document provides an update on the status of these ARM facility enhancements, beginning with the measurement enhancements at the SGP and NSA, followed by a discussion of the modeling project including associated data-processing activities.

Southern Great Plains, North Slope of Alaska, Unma↗
DOE OSTI2020

Striped Data Analysis Framework

A columnar data representation is known to be an efficient way for data storage, specifically in cases when the analysis is often done based only on a small fragment of the available data structures. A data representation like Apache Parquet is a step forward from a columnar representation, which splits data horizontally to allow for easy parallelization of data analysis. Based on the general idea of columnar data storage, working on the [LDRD Project], we have developed a striped data representation, which, we believe, is better suited to the needs of High Energy Physics data analysis. A traditional columnar approach allows for efficient data analysis of complex structures. While keeping all the benefits of columnar data representations, the striped mechanism goes further by enabling easy parallelization of computations without requiring special hardware. We will present an implementation and some performance characteristics of such a data representation mechanism using a distributed no-SQL database or a local file system, unified under the same API and data representation model. The representation is efficient and at the same time simple so that it allows for a common data model and APIs for wide range of underlying storage mechanisms such as distributed no-SQL databases and local file systems. Striped storage adopts Numpy arrays as its basic data representation format, which makes it easy and efficient to use in Python applications. The Striped Data Server is a web service, which allows to hide the server implementation details from the end user, easily exposes data to WAN users, and allows to utilize well known and developed data caching solutions to further increase data access efficiency. We are considering the Striped Data Server as the core of an enterprise scale data analysis platform for High Energy Physics and similar areas of data processing. We have been testing this architecture with a 2TB dataset from a CMS dark matter search and plan to expand it to multiple 100 TB or even PB scale. We will present the striped format, Striped Data Server architecture and performance test results.

Gutsche, Oliver↗
DOE OSTI2026

Performance and Reliability Assessment of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Data Advisor (ADA)

The Atmospheric Radiation Measurement (ARM) User Facility provides one of the world's largest openly accessible repositories of atmospheric observations through the ARM Data Discovery platform. Although the repository contains more than three decades of measurements collected from permanent observatories, mobile facilities, aircraft campaigns, and field experiments, identifying appropriate datasets can be challenging, particularly for new users unfamiliar with ARM instrumentation and datastream organization. To improve data accessibility, the ARM Data Center developed the ARM Data Advisor (ADA), an artificial intelligence-powered assistant designed to facilitate scientific data discovery, dataset interpretation, and user guidance. This report evaluates ADA's performance as a domain-specific scientific assistant using realistic atmospheric science workflows. The evaluation examines five key capabilities: data retrieval and curation efficiency, hallucination resistance, scientific reasoning, response to ambiguous queries, and content retention and session continuity. Representative prompts were developed to simulate typical interactions between researchers and the ARM Data Discovery platform, and ADA's responses were assessed for retrieval completeness, scientific accuracy, consistency, and practical usefulness. In these representative tests, ADA reduced the complexity of discovering and accessing ARM datasets by recommending appropriate datastreams, explaining instrumentation, interpreting metadata, and assisting with data processing workflows. ADA also exhibits strong domain knowledge of atmospheric science terminology and generally resists hallucination by acknowledging unavailable datasets and requesting clarification when appropriate. Overall, the results indicate that ADA represents a promising advancement in scientific data discovery within the ARM User Facility and has considerable potential to improve researcher productivity, particularly for new users and interdisciplinary scientists seeking efficient access to ARM observations.

Salvador, Christian [ORNL] (ORCID:0000000283287777↗
DOE OSTI2019

Advances in Nuclear Radiation Sensing: Enabling 3-D Gamma-Ray Vision

The enormous advances in sensing and data processing technologies in combination with recent developments in nuclear radiation detection and imaging enable unprecedented and “smarter” ways to detect, map, and visualize nuclear radiation. The recently developed concept of three-dimensional (3-D) Scene-data fusion allows us now to “see” nuclear radiation in three dimensions, in real time, and specific to radionuclides. It is based on a multi-sensor instrument that is able to map a local scene and to fuse the scene data with nuclear radiation data in 3-D while the instrument is freely moving through the scene. This new concept is agnostic of the deployment platform and the specific radiation detection or imaging modality. We have demonstrated this 3-D Scene-data fusion concept in a range of configurations in locations, such as the Fukushima Prefecture in Japan or Chernobyl in Ukraine on unmanned and manned aerial and ground-based platforms. It provides new means in the detection, mapping, and visualization of radiological and nuclear materials relevant for the safe and secure operation of nuclear and radiological facilities or in the response to accidental or intentional releases of radioactive materials where a timely, accurate, and effective assessment is critical. In addition, the ability to visualize nuclear radiation in 3-D and in real time provides new means in the communication with public and facilitates to overcome one of the major public concerns of not being able to “see” nuclear radiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Minimizing Error Potential Using Computer Applications - 18498

Many Savannah River Site (SRS) liquid waste facility operations depend upon repetitive engineering calculations and operator actions. Although these calculations and actions are formalized in technical reports and paper procedures, they can still be vulnerable to data entry errors, calculation errors, equipment alignment errors, and occasional changes caused by different people performing these activities. Savannah River Remediation (SRR) is using computer automation to reduce these error precursors by standardizing repetitive calculations and by performing plant alignment checks for repetitive operation processes. Data entry can be automated, calculation methodologies can be standardized, and computers can check to see that predefined plant conditions exist before equipment operation. In addition to improving quality, the time required for these activities to generate technical reports, to perform independent reviews, and to perform equipment alignment checks can be significantly reduced. In the case of operator-performed calculations, error precursors involve distractions that can occur over a multi-page paper procedure, confusing displays and controls from equipment, mathematical errors, complacency, and unfamiliarity with the procedure among many others. Repetitive engineering calculations suffer from similar error precursors and are often compounded by high workloads, lack of proficiency, lack of standard methodology, mental shortcuts, and biases. Web-based computer applications can eliminate many of these precursors through standardization. Calculation methods are fixed, inputs are fixed, and computer checks can highlight potentially wrong inputs and outputs. Automated calculations are performed almost instantaneously once input is provided. Operators and engineers can spend more time focusing on the results than on the process to achieve the results. Similarly, when operators use repetitive procedures involving equipment manipulation, the same error precursors apply. Automated operation sequences and equipment checks can be programmed into the distributed control system to provide standard operating processes that reduce and eliminate error precursors. This paper describes how SRR incorporates Human Performance Improvement (HPI) principles when automating calculations and operation processes. Computer applications will be reviewed in detail, highlighting the software development life-cycle that includes requirements gathering, prototyping, design, development, testing, and implementation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

SU-E-T-474: IMRT Verification Using the On-Board EPID

Purpose: To verify IMRT and Rapid Arc (RA) plan's agreement with treatment delivery for radiation therapy using an on-board EPID compared to MapCHECK2 and ArcCHECK. Methods: On-board EPID (Exact arm) is commissioned using manufacturer's Preconfigured Data Input Package (PDIP). Portal dose calculation engine for comparison with measurement was commissioned with PDIP. The absolute dosimetric calibration of the EPID is performed using 10×10cm field size at 105cm source to image detector distance with 90.7 CU in the integrated mode. The dark and flood field of EPID were also calibrated in the integrated mode for all energies and dose rates. The output dose-response data from the manufacturer was verified. The improved gamma test method was used for EPID data analysis. Gamma test were used for MapCHECK2 (or ArcCHECK). The sensitivity of the method was tested using collimator rotation at 3 degree and 5 degree. Student T-test was used to distinguish the difference among the groups. Results: IMRT: The average of Gamma passing rate using EPID and MapCHECK2 is 98.9±1.6% and 98.7±2.0% (p = 0.342). There is no statistical difference between two groups.RA: The average of Gamma passing rate using EPID and ArcCHECK is 97.2±2.3% and 93.2±4.1%. (p = 0.002). EPID significantly improved the RapidARC plan passing rate compared to the ArcCHECK. 5% dose change typically causes between 3 – 55% change in Gamma. Conclusion: Using the EPID, we were able to perform QA verification on IMRT plans comparable to MapCHECK2 (p=0.342) and superior to that of ArcCHECK (p=0.002) using Gamma 3%, 3mm criteria. The sensitivity of EPID was found to be comparable to that of the MapCHECK2 and ArcCHECK. EPID dosimetry is faster (4.3 mins vs. 10 mins) due to easier setup and integrated data processing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Multi-Scale Integrated Monitoring System for Enhancing Methane Emission Detection, Quantification & Prediction

This report details the progress and findings of a comprehensive study on reviewing existing solutions, identifying technology gaps, and formulating an “all-in-one” integrated strategy for developing the next-generation multiscale methane monitoring and modeling platform, conducted under grant number DE-FE0032292. Co-led by Dr. David Ebert, Dr. Binbin Weng, and Dr. Chenghao Wang at the University of Oklahoma, the project’s goal was to develop an integrated approach for building this engineering platform to detect, quantify, and mitigate methane emissions across various temporal scale, spatial scales, and sectors. The planning grant study began with an extensive review of various methane sensing and monitoring technologies and systems, surveying over 100 technology providers globally. This review revealed the prevalence of optical methods over chemical methods in commercially available sensors, with Non-Dispersive Infrared (NDIR), Tunable Diode Laser Absorption Spectroscopy (TDLAS), and Optical Gas Imaging (OGI) cameras being the most prevalent options. A trend towards more advanced optical techniques was observed, driven by increased regulatory focus and technological advancements. The technical evaluation of these sensing technologies provided crucial insights into their capabilities and limitations. The study examined emerging technologies such as Differential Absorption LiDAR (DIAL), which show promise for high-precision and long-range detection. The team then investigated the features and application bandwidth of various sensing platforms, including handheld, fixed/stationary, mobile, aerials, and spaceborne monitors. Pilot field studies were conducted to assess the capabilities of solutions for different emission scenarios. Field work with sensor deployments was conducted at three distinct site types: an oil & gas industry site, a cattle ranching operation, and a waste processing facility. The team also conducted a thorough review of methane flux inverse modeling approaches, focused on physically based methods. These approaches were categorized into simple, intermediate, and advanced methods. A realtime WRF-GHG (Weather Research and Forecasting-Greenhouse Gas) modeling system was developed and applied, incorporating multiple data sources to guide field experiments and inform methane plume detection. The project identified and analyzed numerous categories of methane data sources, including satellite measurements, ground-based sensors, and inventory databases. Key platforms examined include EDGAR, EPA GHGI, NASA TROPOMI, Carbon Mapper, and Climate TRACE, among others. The team proposed an architecture for a comprehensive methane monitoring platform. This system incorporates multi-source data acquisition, advanced data processing and assimilation, interactive visualization tools, and analytical capabilities for emissions forecasting and scenario analysis. The proposed platform aims to provide a user-friendly interface catering to various stakeholders, from researchers to policymakers. The architecture includes sophisticated data ingestion methods, a centralized data warehouse, and advanced analytical tools for data fusion and interpretation. To ensure the relevance and effectiveness of the proposed system, a comprehensive survey was conducted to gather stakeholder input on system requirements. Key findings include a strong need for integrating various data types and formats, a preference for real-time data updates and advanced visualization tools, and a demand for user-friendly interfaces catering to different expertise levels.

03 NATURAL GAS↗
DOE OSTI2024

Ground far-red sun-induced chlorophyll fluorescence and vegetation indices in the US Midwestern agroecosystems

Abstract Sun-induced chlorophyll fluorescence (SIF) provides an opportunity to study terrestrial ecosystem photosynthesis dynamics. However, the current coarse spatiotemporal satellite SIF products are challenging for mechanistic interpretations of SIF signals. Long-term ground SIF and vegetation indices (VIs) are important for satellite SIF validation and mechanistic understanding of the relationship between SIF and photosynthesis when combined with leaf- and canopy-level auxiliary measurements. In this study, we present and analyze a total of 15 site-years of ground far-red SIF (SIF at 760 nm, SIF 760 ) and VIs datasets from soybean, corn, and miscanthus grown in the U.S. Corn Belt from 2016 to 2021. We introduce a comprehensive data processing protocol, including different retrieval methods, calibration coefficient adjustment, and nadir SIF footprint upscaling to match the eddy covariance footprint. This long-term ground far-red SIF and VIs dataset provides important and first-hand data for far-red SIF interpretation and understanding the mechanistic relationship between far-red SIF and canopy photosynthesis across various crop species and environmental conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Azura WEC 1/15th Wave Tank Test Data

Test data from the 1/15th Wave Tank Tests of the Azura performed in 2017/2018 to validate the power performance and survivability of the Azura Design planned for deployment at the US Navy's Wave Energy Test Site. Raw and processed data included, along with test plan, test report, and summary data in the content model: "WEC Lab Testing content Model".

16 TIDAL AND WAVE POWER↗
DOE OSTI2013

Aerial Measuring System (AMS)/Israel Atomic Energy Commission (IAEC) Joint Comparison Study Report

Under the 13th Bilateral Meeting to Combat Nuclear Terrorism conducted on January 8–9, 2013, the committee approved the development of a cost-effective proposal to conduct a Comparison Study of the Aerial Measuring System (AMS) of the U.S. Department of Energy (DOE), National Nuclear Security Administration (NNSA) and Israel Atomic Energy Commission (IAEC). The study was to be held at the Remote Sensing Laboratory (RSL), Nellis Air Force Base, Las Vegas, Nevada, with measurements at the Nevada National Security Site (NNSS). The goal of the AMS and the IAEC joint survey was to compare the responses of the two agencies’ aerial radiation detection systems to varied radioactive surface contamination levels and isotopic composition experienced at the NNSS, and the differing data processing techniques utilized by the respective teams. Considering that for the comparison both teams were using custom designed and built systems, the main focus of the short campaign was to investigate the impact of the detector size and data analysis techniques used by both teams. The AMS system, SPectral Advanced Radiological Computer System, Model A (SPARCS-A), designed and built by RSL, incorporates four different size sodium iodide (NaI) crystals: 1" × 1", 2" × 4" × 4", 2" × 4" ×16", and an “up-looking” 2" × 4" × 4". The Israel AMS System, Air RAM 2000, was designed by the IAEC Nuclear Research Center – Negev (NRCN) and built commercially by ROTEM Industries (Israel) and incorporates two 2" diameter × 2" long NaI crystals. The operational comparison was conducted at RSL-Nellis in Las Vegas, Nevada, during week of June 24–27, 2013. The Israeli system, Air RAM 2000, was shipped to RSL-Nellis and mounted together with the DOE SPARCS on a DOE Bell-412 helicopter for a series of aerial comparison measurements at local test ranges, including the Desert Rock Airport and Area 3 at the NNSS. A 4-person Israeli team from the IAEC NRCN supported the activity together with 11 members of the RSL team, which consisted of pilots, mechanics, scientists, a data analyst, equipment operators, and operation specialists. All planned flight activities followed by scientific discussions on the collected data were completed. For IAEC, the joint survey provided an opportunity to characterize their system’s response to extended sources of various fission products at the NNSS. As both systems play an important role in their respective countries’ (United States and Israel) national framework of radiological emergency response and are subject to multiple mutual cooperation agreements, it was important for each country to obtain more thorough knowledge of how they would employ these important assets and define the roles that they would each play in an actual response.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

The structure of the ternary Eg5–ADP–ispinesib complex

The complex between the motor protein Eg5 and the phase II clinical candidate ispinesib provides insights into the mechanism of action of this important class of inhibitors. The human kinesin Eg5 is responsible for bipolar spindle formation during early mitosis. Inhibition of Eg5 triggers the formation of monoastral spindles, leading to mitotic arrest that eventually causes apoptosis. There is increasing evidence that Eg5 constitutes a potential drug target for the development of cancer chemotherapeutics. The most advanced Eg5-targeting agent is ispinesib, which exhibits potent antitumour activity and is currently in multiple phase II clinical trials. In this study, the crystal structure of the Eg5 motor domain in complex with ispinesib, supported by kinetic and thermodynamic binding data, is reported. Ispinesib occupies the same induced-fit pocket in Eg5 as other allosteric inhibitors, making extensive hydrophobic interactions with the protein. The data for the Eg5–ADP–ispinesib complex suffered from pseudo-merohedral twinning and revealed translational noncrystallographic symmetry, leading to challenges in data processing, space-group assignment and structure solution as well as in refinement. These complications may explain the lack of available structural information for this important agent and its analogues. The present structure represents the best interpretation of these data based on extensive data-reduction, structure-solution and refinement trials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗