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A modern Monte Carlo investigation of the TG-43 dosimetry parameters for an {sup 125}I seed already having AAPM consensus data

Purpose: To investigate potential causes for differences in TG-43 brachytherapy dosimetry parameters in the existent literature for the model IAI-125A{sup 125}I seed and to propose new standard dosimetry parameters. Methods: The MCNP5 code was used for Monte Carlo (MC) simulations. Sensitivity of dose distributions, and subsequently TG-43 dosimetry parameters, was explored to reproduce historical methods upon which American Association of Physicists in Medicine (AAPM) consensus data are based. Twelve simulation conditions varying{sup 125}I coating thickness, coating mass density, photon interaction cross-section library, and photon emission spectrum were examined. Results: Varying{sup 125}I coating thickness, coating mass density, photon cross-section library, and photon emission spectrum for the model IAI-125A seed changed the dose-rate constant by up to 0.9%, about 1%, about 3%, and 3%, respectively, in comparison to the proposed standard value of 0.922 cGy h{sup −1} U{sup −1}. The dose-rate constant values by Solberg et al. [“Dosimetric parameters of three new solid core {sup 125}I brachytherapy sources,” J. Appl. Clin. Med. Phys. 3, 119–134 (2002)], Meigooni et al. [“Experimental and theoretical determination of dosimetric characteristics of IsoAid ADVANTAGE™ {sup 125}I brachytherapy source,” Med. Phys. 29, 2152–2158 (2002)], and Taylor and Rogers [“An EGSnrc Monte Carlo-calculated database of TG-43 parameters,” Med. Phys. 35, 4228–4241 (2008)] for the model IAI-125A seed and Kennedy et al. [“Experimental and Monte Carlo determination of the TG-43 dosimetric parameters for the model 9011 THINSeed™ brachytherapy source,” Med. Phys. 37, 1681–1688 (2010)] for the model 6711 seed were +4.3% (0.962 cGy h{sup −1} U{sup −1}), +6.2% (0.98 cGy h{sup −1} U{sup −1}), +0.3% (0.925 cGy h{sup −1} U{sup −1}), and −0.2% (0.921 cGy h{sup −1} U{sup −1}), respectively, in comparison to the proposed standard value. Differences in the radial dose functions between the current study and both Solberg et al. and Meigooni et al. were <10% for r ≤ 5 cm, and increased for r > 5 cm with a maximum difference of 29% at r = 9 cm. In comparison to Taylor and Rogers, these differences were lower (maximum of 2% at r = 9 cm). For the similarly designed model 6711 {sup 125}I seed, differences did not exceed 0.5% for 0.5 ≤ r ≤ 10 cm. Radial dose function values varied by 1% as coating thickness and coating density were changed. Varying the cross-section library and source spectrum altered the radial dose function by 25% and 12%, respectively, but these differences occurred at r = 10 cm where the dose rates were very low. The 2D anisotropy function results were most similar to those of Solberg et al. and most different to those of Meigooni et al. The observed order of simulation condition variables from most to least important for influencing the 2D anisotropy function was spectrum, coating thickness, coating density, and cross-section library. Conclusions: Several MC radiation transport codes are available for calculation of the TG-43 dosimetry parameters for brachytherapy seeds. The physics models in these codes and their related cross-section libraries have been updated and improved since publication of the 2007 AAPM TG-43U1S1 report. Results using modern data indicated statistically significant differences in these dosimetry parameters in comparison to data recommended in the TG-43U1S1 report. Therefore, it seems that professional societies such as the AAPM should consider reevaluating the consensus data for this and others seeds and establishing a process of regular evaluations in which consensus data are based upon methods that remain state-of-the-art.

61 RADIATION PROTECTION AND DOSIMETRY↗

Data reduction for low energy nuclear physics experiments using data frames

Low energy nuclear physics experiments are transitioning towards fully digital data acquisition systems. Realizing the gains in flexibility afforded by these systems relies on equally flexible data reduction techniques. In this paper, methods utilizing data frames and in-memory techniques to work with data, including data from self-triggering, digital data acquisition systems, are discussed within the context of a Python package, sauce. It is shown that data frame operations can encompass common analysis needs and allow interactive data analysis. Two event building techniques, dubbed referenced and referenceless event building, are shown to provide a means to transform raw list mode data into correlated multi-detector events. These techniques are demonstrated in the analysis of two example data sets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Putting Our Industry's Data to Work: A Case Study of Large-Scale Data Aggregation: Preprint

With increasing deployment of Advanced Metering Infrastructure (AMI), Building Automation System (BAS) controls, Internet of Things (IoT) network devices, and data-driven evaluation, measurement, and verification studies, the building sector is currently generating a staggering amount of energy-related data. In the right hands, these data sets can contribute to increased comfort and energy savings for building occupants and a more reliable electrical grid; however, due to a combination of factors, including significant privacy concerns, much of the data that are presently generated and stored are not used outside of basic operational applications. In the past year, our team has dedicated over 2,000 person-hours to accessing building energy data for a project funded by the U.S. Department of Energy (DOE) Building Technologies Office. We sought whole-building or end-use (e.g., lighting) timeseries data at the individual-building or equipment level where possible or aggregated information, such as timeseries averages and quartiles by building type (e.g., office, retail, hospital), where sharing individual building information was not an option. We are additionally working with IoT and BAS data sets to derive information important to the project. We have assembled an extensive data set that will enable the development of publicly available end-use load profiles to benefit the U.S. building and electricity industries. Here we present an overview of the data set that we have assembled to date, the motivators and approaches that got us here, and the lessons we learned through our efforts. We also discuss work underway that presents additional options for future data access.

building energy data↗

Transportation Secure Data Center: Real-World Data for Planning, Modeling, and Analysis

The Transportation Secure Data Center (TSDC) provides free, web-based access to detailed transportation data from a variety of travel surveys conducted across the nation. While preserving the privacy of survey participants, this online repository makes vital transportation data broadly available to users from the comfort of their own desks via a secure online connection. Maintained by the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) in partnership with the U.S. Department of Transportation (DOT), the TSDC houses data from travel surveys and studies conducted using global positioning system (GPS) devices. It features millions of data points - second-by-second GPS readings, vehicle characteristics (if applicable), and demographics - for all modes of travel. NREL screens the initial data for quality control, translates each data set into a consistent format, and interprets the data for spatial analysis. NREL's processing routines add information on vehicle fuel economy and road grades and join data points to the road network.

30 DIRECT ENERGY CONVERSION↗

Advanced data science toolkit for non-data scientists – A user guide

Emerging modern data analytics attracts much attention in materials research and shows great potential for enabling data-driven design. Data populated from the high-throughput CALPHAD approach enables researchers to better understand underlying mechanisms and to facilitate novel hypotheses generation, but the increasing volume of data makes the analysis extremely challenging. Here in this paper, we introduce an easy-to-use, versatile, and open-source data analytics frontend, ASCENDS (Advanced data SCiENce toolkit for Non-Data Scientists), designed with the intent of accelerating data-driven materials research and development. The toolkit is also of value beyond materials science as it can analyze the correlation between input features and target values, train machine learning models, and make predictions from the trained surrogate models of any scientific dataset. Various algorithms implemented in ASCENDS allow users performing quantified correlation analyses and supervised machine learning to explore any datasets of interest without extensive computing and data science background. The detailed usage of ASCENDS is introduced with an example of experimental high-temperature alloy data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques

By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data which violates statistical assumptions for many of the methods currently used to analyze these data such as linear regression, analysis of variance, and t-tests. These data are inherently multivariate and non-negative parts of a whole. This paper introduces the field of compositional data analysis to the emissions community and provides examples of appropriate statistical treatment of emissions data. It is shown that modified combustion efficiency should not be used as a predictor variable for other smoke emissions because it is not an independent variable. An alternative method based on compositional linear trends to estimate trace gas composition using CO and CO2 is presented. The data used in this paper resulted from projects the DOD/DOE/EPA Strategic 586 Environmental Research and Development Program projects RC-1648 and 1649. The senior 587 author appreciates the guidance and R scripts provided by Prof. Girty at San Diego State 588 University to estimate linear trends by perturbation. J. P.-A. was supported by the Spanish 589 Ministry of Science, Innovation and Universities under the project CODAMET (RTI2018-590 095518-B-C21, 2019-2021). The data used in this study have been previously published and are 591 available in the original publications. DRW conceived the initial manuscript (70 percent) and 592 performed the bulk of the data analysis. JPA provided statistical guidance and compositional data 593 expertise and contributed 20 percent of the manuscript. TJJ and HJ were extensively involved in 594 the study that provided the data. TJJ provide smoke emissions expertise and HJ provided 595 combustion expertise. The authors declare that they have no conflict of interest. The use of trade 596 or firm names in this publication is for reader information and does not imply endorsement by 597 the U.S. Department of Agriculture of any product or service.

simplex, compositional data analysis, balance, log↗

A fast two-stage algorithm for non-negative matrix factorization in smoothly varying data

This article reports the study of algorithms for non-negative matrix factorization (NMF) in various applications involving smoothly varying data such as time or temperature series diffraction data on a dense grid of points. Utilizing the continual nature of the data, a fast two-stage algorithm is developed for highly efficient and accurate NMF. In the first stage, an alternating non-negative least-squares framework is used in combination with the active set method with a warm-start strategy for the solution of subproblems. In the second stage, an interior point method is adopted to accelerate the local convergence. The convergence of the proposed algorithm is proved. The new algorithm is compared with some existing algorithms in benchmark tests using both real-world data and synthetic data. Furthermore, the results demonstrate the advantage of the algorithm in finding high-precision solutions.

interior point method↗

Completeness and coverage of open-access freshwater fish distribution data in the United States

Aim: Primary biodiversity data constitute observations of particular species at given points in space and time. Open-access databases provide unprecedented access to these data, but their utility depends on how complete species inventories are at a given surveying resolution and how uniformly distributed surveys are in space and time. Our aim was to characterize the completeness of freshwater fish data across spatial scales and among habitat types (lotic stream reaches and lentic waterbodies), and assess coverage bias in space and time. Location: Freshwater habitats of the contiguous United States. Methods: We compiled fish occurrence records from the Global Biodiversity Information Facility (GBIF), the Multi-state Aquatic Resources Information Server (MARIS), and three federally-administered surveys (EMAP, NAQWA, NRS). Next, we evaluated survey completeness across seven spatial resolutions representing nested stream catchments, and separately for lotic and lentic habitats. Lastly, we tested for bias in survey coverage along environmental and temporal gradients for each habitat type. Results: A total of 39,855,157 records representing 1925 species were available from 1800 to 2014. The percent of catchments surveyed increased as spatial resolution decreased while the density of occurrence records within surveyed catchments decreased. Species richness also increased with catchment size consistent with putative species–area relationships. Occurrence records were distributed among 72,114 lotic reaches and 3,325 lentic waterbodies throughout the contiguous US. Seven percent (N=5,055) of surveyed lotic reaches and 23% (N=771) of surveyed lentic waterbodies were well-surveyed based on the most conservative thresholds for two completeness indices. Most well-surveyed lotic reaches (95%) and undammed lentic waterbodies (97%) were completed since 1980, and most were surveyed during only one 20-year time interval (83% and 56% for lotic and lentic waterbodies, respectively). Coverage analyses indicated that contemporary and future climates corresponding to regions along the west coast and gulf coast are the most under-represented for both lotic and lentic habitats. Small lentic waterbodies (surface area < 0.1 km2) are also under-represented. Main Conclusions: Contemporary surveys of lotic reaches and, to a lesser extent, lentic waterbodies are plentiful and generally representative of climatic and landscape characteristics. Data compilation efforts should focus on adding historical data to public repositories. Clustering of well-surveyed waterbodies in MARIS-participating states highlights the value of state-agency data and demonstrates the need for dissemination of these data by more state agencies.

60 APPLIED LIFE SCIENCES↗

Countering Weapons of Mass Destruction Office (CWMD) Data Categorization Study: Chemical, Biological, Radiological, and Nuclear (CBRN) Detection Device Data

Pacific Northwest National Laboratory (PNNL) seeks to address critical questions related to chemical, biological, radiological, and nuclear (CBRN) detection devices. This research aims to enhance the security and understanding of these devices by investigating various aspects of their identification, communication, and functionality. The primary focus is on network security, malware detection, device identification, and intelligence gathering. CBRN data can be categorized in various ways depending on the purpose of CBRN detection devices and the specific context of the applications for analysis. Criteria that can be used to assist in this effort include but are not limited to data type, data protocol, source/destination, application, time, security, and content. This study will inform additional paths for data classification, data profiling, data mapping, and data modeling. This will help the Countering Weapons of Mass Destruction Office (CWMD) better understand their data and make informed decisions based on the insights gained from this study and their application. The CBRN Data Categorization study will include the identification of 5–10 different CBRN detection devices with unique characteristics for assessing and analyzing the data that is being produced by and transmitted from these devices.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

National Geothermal Data System (NGDS) Geothermal Data: Community Requirements and Information Engineering

To satisfy the critical need for geothermal data to advance geothermal energy as a viable renewable energy contender, the U.S. Department of Energy is investing in the development of the National Geothermal Data System (NGDS). This paper outlines efforts among geothermal data providers nationwide to supply cutting edge geo-informatics. NGDS geothermal data acquisition, delivery, and methodology are discussed. In particular, this paper addresses the various types of data required to effectively assess geothermal energy potential and why simple links to existing data are insufficient. To create a platform for ready access by all geothermal stakeholders, the NGDS includes a work plan that addresses data assets and resources of interest to users, a survey of data providers, data content models, and how data will be exchanged and promoted, as well as lessons learned within the geothermal community.

15 GEOTHERMAL ENERGY↗

DOE Geothermal Data Repository: Getting More Mileage Out of Your Data: Preprint

All data submitted to the U.S. Department of Energy's Geothermal Data Repository (GDR) is eventually made public. The metadata for these data submissions is searchable in multiple data catalogs, including the GDR catalog and the data catalog on OpenEI.org. Because it is a node on the National Geothermal Data System (NGDS), all data on the GDR are also discoverable through both the regular Identifier (DOI), and as a byproduct of this assignment, these submissions are automatically registered in the Office of Science and Technical Information (OSTI) DataCite catalog. From there, these data are federated to additional sites both domestic and international, including Science.gov and WorldWideScience.org. This paper will explore in detail the wide reach of data submitted to the GDR from and how this exposure can dramatically increase the utility of submitted data.

15 GEOTHERMAL ENERGY↗

ActiveSpaces: Exploring dynamic code deployment for extreme scale data processing: ActiveSpaces: Exploring dynamic code deployment for extreme scale data processing

Managing the large volumes of data produced by emerging scientific and engineering simulations running on leadership-class resources has become a critical challenge. The data have to be extracted off the computing nodes and transported to consumer nodes so that it can be processed, analyzed, visualized, archived, and so on. Several recent research efforts have addressed data-related challenges at different levels. One attractive approach is to offload expensive input/output operations to a smaller set of dedicated computing nodes known as a staging area. However, even using this approach, the data still have to be moved from the staging area to consumer nodes for processing, which continues to be a bottleneck. In this paper, we investigate an alternate approach, namely moving the data-processing code to the staging area instead of moving the data to the data-processing code. Specifically, we describe the ActiveSpaces framework, which provides (1) programming support for defining the data-processing routines to be downloaded to the staging area and (2) runtime mechanisms for transporting codes associated with these routines to the staging area, executing the routines on the nodes that are part of the staging area, and returning the results. We also present an experimental performance evaluation of ActiveSpaces using applications running on the Cray XT5 at Oak Ridge National Laboratory. Finally, we use a coupled fusion application workflow to explore the trade-offs between transporting data and transporting the code required for data processing during coupling, and we characterize sweet spots for each option.

97 MATHEMATICS AND COMPUTING↗

The Data Mine model for accessible partnerships in data science

Abstract The Data Mine at Purdue University is a pioneering experiential learning community for undergraduate and graduate students of any background to learn data science. The first data‐intensive experience embedded in a large learning community, The Data Mine had nearly 1300 students in academic year (AY) 2022–2023 and nearly 1700 students for AY 2023–2024. The Data Mine embodies data‐infused education, research, and collaboration. Students learn Python, R, SQL, and shell‐scripting, while working on weekly projects within a high‐performance computing (HPC) cluster. In the Corporate Partners cohort, students work on teams of 5–15 students, led by a paid student team leader. Each cohort follows an Agile approach, working on data‐intensive projects provided by industry partners and mentored by company employees. Students develop professional and data skills throughout the academic year, from August through April. Many students return in subsequent years to the program, increasing their tenure with a Corporate Partner. Student teams are inherently interdisciplinary; students from 133 different majors are involved in the program, ranging from new incoming students through PhD level students. These interdisciplinary teams of students bring new perspectives to challenging problems in which data science is a key part of the solution. The interdisciplinary teams foster an environment of synthesis with ideas and solutions. Students come together with different life experiences, different levels of technical skill, but also varying ways they navigate paths to solutions because of the variety of majors represented, resulting in a more creative and robust solution than a traditional data science program. This article is categorized under: Applications of Computational Statistics > Education in Computational Statistics

Betz, Margaret A.↗

Nuclear Data Sheets for A=218

The evaluated data are presented for 11 known A=218 nulcides (Pb, Bi, Po, At, Rn, Fr, Ra, Ac, Th, Pa and U). For {sup 218}Pb, {sup 218}Bi, {sup 218}At and {sup 218}Pa, data are available only for the ground states. For {sup 218}U, only the g.s. and a high-spin isomer are known, with no data on γ-ray transitions available. For {sup 218}Po, ten excited states are known from {sup 218}Bi decay, with no knowledge on the multipolarities of gamma-ray transitions. For {sup 218}Th, five excited states in the g.s. band are known from an in-beam γ-ray study. Data on level half-lives, multipolarities and mixing ratios of gamma transitions is generally lacking for A=218 nuclei. The static magnetic dipole moment has been measured for only an isomer in {sup 218}Fr. With the exception of a new nuclide, {sup 218}Pb, and measurements of half-lives of ground states of a few nuclides of A=218 and A=222, no substantial structure information has become available since the previous evaluation in 2006. Q values are adopted from 2017Wa10 (AME-2016). The present evaluation supersedes the previous A=218 ENSDF evaluations, 2006Ja03, 1995El08, 1987El12 and 1977To13. This evaluation was carried out as part of a joint IAEA-ICTP workshop for Nuclear Structure and Decay Data, organized and hosted by the IAEA, Vienna, and ICTP, Trieste, October 15–26, 2018.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Use of genomic data in risk assessment case study: II. Evaluation of the dibutyl phthalate toxicogenomic data set

An evaluation of the toxicogenomic data set for dibutyl phthalate (DBP) and male reproductive developmental effects was performed as part of a larger case study to test an approach for incorporating genomic data in risk assessment. The DBP toxicogenomic data set is composed of nine in vivo studies from the published literature that exposed rats to DBP during gestation and evaluated gene expression changes in testes or Wolffian ducts of male fetuses. The exercise focused on qualitative evaluation, based on a lack of available dose–response data, of the DBP toxicogenomic data set to postulate modes and mechanisms of action for the male reproductive developmental outcomes, which occur in the lower dose range. A weight-of-evidence evaluation was performed on the eight DBP toxicogenomic studies of the rat testis at the gene and pathway levels. The results showed relatively strong evidence of DBP-induced downregulation of genes in the steroidogenesis pathway and lipid/sterol/cholesterol transport pathway as well as effects on immediate early gene/growth/differentiation, transcription, peroxisome proliferator-activated receptor signaling and apoptosis pathways in the testis. Since two established modes of action (MOAs), reduced fetal testicular testosterone production and Insl3 gene expression, explain some but not all of the testis effects observed in rats after in utero DBP exposure, other MOAs are likely to be operative. A reanalysis of one DBP microarray study identified additional pathways within cell signaling, metabolism, hormone, disease, and cell adhesion biological processes. These putative new pathways may be associated with DBP effects on the testes that are currently unexplained. This case study on DBP identified data gaps and research needs for the use of toxicogenomic data in risk assessment. Furthermore, this study demonstrated an approach for evaluating toxicogenomic data in human health risk assessment that could be applied to future chemicals. - Highlights: ► We evaluate the dibutyl phthalate toxicogenomic data for use in risk assessment. ► We focus on information about the mechanism of action for the developing testis. ► Multiple studies report effects on testosterone and insl3-related pathways. ► We identify additional affected pathways that may explain some testis effects. ► The case study is a template for evaluating toxicogenomic data in risk assessment.

60 APPLIED LIFE SCIENCES↗

Polar Liquid Cloud Base Detection Algorithms for High Spectral Resolution or Micropulse Lidar Data

Liquid layers in clouds affect their microphysical processes, as well as the atmospheric energy budget. However, explicit liquid cloud base height (LCBH) detection algorithms using ground-based instruments (e.g., lidars) are currently absent in the literature. Most studies use either fixed lidar parameter thresholds or cloud base height data products that do not distinguish between ice and liquid, all of which might introduce inconsistencies and errors in the resolved LCBHs. In this paper, two LCBH detection algorithms are presented; the first algorithm uses the high spectral resolution lidar (HSRL) data, and yields satisfactory results. The second algorithm incorporates micropulse lidar (MPL) data for the LCBH detection. A 1-year long comparison of data gathered at Barrow, Alaska, and McMurdo Station, Antarctica, which includes other cloud base detection methodologies (ceilometer, MPL value-added product cloud base height, LCBHs detected using a fixed MPL depolarization threshold) emphasize the merits of the MPL algorithm.

Silber, Israel↗

Enabling FAIR data in Earth and environmental science with community-centric (meta)data reporting formats

Abstract Research can be more transparent and collaborative by using Findable, Accessible, Interoperable, and Reusable (FAIR) principles to publish Earth and environmental science data. Reporting formats—instructions, templates, and tools for consistently formatting data within a discipline—can help make data more accessible and reusable. However, the immense diversity of data types across Earth science disciplines makes development and adoption challenging. Here, we describe 11 community reporting formats for a diverse set of Earth science (meta)data including cross-domain metadata (dataset metadata, location metadata, sample metadata), file-formatting guidelines (file-level metadata, CSV files, terrestrial model data archiving), and domain-specific reporting formats for some biological, geochemical, and hydrological data (amplicon abundance tables, leaf-level gas exchange, soil respiration, water and sediment chemistry, sensor-based hydrologic measurements). More broadly, we provide guidelines that communities can use to create new (meta)data formats that integrate with their scientific workflows. Such reporting formats have the potential to accelerate scientific discovery and predictions by making it easier for data contributors to provide (meta)data that are more interoperable and reusable.

54 ENVIRONMENTAL SCIENCES↗

Cosmic ray propagation and dark matter in light of the latest AMS-02 data

The AMS-02 experiment is measuring the high energy cosmic rays with unprecedented accuracy. We explore the possibility of determining the cosmic-ray propagation models using the AMS-02 data alone. A global Bayesian analysis of the constraints on the cosmic-ray propagation models from the preliminary AMS-02 data on the Boron to Carbon nuclei flux ratio and proton flux is performed, with the assumption that the primary nucleon source is a broken power law in rigidity. The ratio of the diffusion coefficient D{sub 0} to the diffusive halo height Z{sub h} is determined with high accuracy D{sub 0}/Z{sub h}≃2.00±0.07 cm{sup 2}s{sup −1}kpc{sup −1}, and the value of the halo width is found to be Z{sub h}≃3.3 kpc with uncertainty less than 50%. As a consequence, the typical uncertainties in the positron fraction predicted from dark matter (DM) annihilation is reduced to a factor of two, and that in the antiproton flux is about an order of magnitude. Both of them are significantly smaller than that from the analyses prior to AMS-02. Taking into account the uncertainties and correlations in the propagation parameters, we derive conservative upper limits on the cross sections for DM annihilating into various standard model final states from the current PAMELA antiproton data. We also investigate the reconstruction capability of the future high precision AMS-02 antiproton data on the DM properties. The results show that for DM particles lighter than ∼100 GeV and with typical thermal annihilation cross section, the cross section can be well reconstructed with uncertainties about a factor of two for the AMS-02 three-year data taking.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗