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At least 649 records · Page 36

$\mathrm{D}$ark$\mathrm{F}$lux: A new tool to analyze indirect-detection spectra of next-generation dark matter models

Here we present DarkFlux, a software tool designed to analyze indirect-detection signatures for next-generation models of dark matter (DM) with multiple annihilation channels. Version 1.0 of this tool accepts user-generated models with 2→2 tree-level dark matter annihilation to pairs of Standard Model (SM) particles and analyzes DM annihilation to γ rays. The tool consists of three modules, which can be run in a loop in order to scan over DM mass if desired: The annihilation fraction module calls an internal installation of MadDM, a dark matter phenomenology plugin for the Monte Carlo event generator MadGraph5 _ aMC@NLO, to compute the thermally averaged cross section $\langle σv\rangle_i$ for each annihilation channel $χχ$ ($\bar{χ}$,$χ^†$)→ i $\∈{SM, SM}. . The module then computes the fractional annihilation rate (annihilation fraction) into each channel. The flux module combines the flux spectrum from each annihilation channel, weighted by the appropriate annihilation fractions, to compute the total flux at Earth due to DM annihilation. In DarkFlux v1.0, this module specifically computes the γ-ray flux for each channel using the publicly available PPPC4DMID tables. The analysis module compares the total flux to observational data and computes the upper limit at 95% confidence level (CL) on the total thermally averaged DM annihilation cross section. In DarkFlux v1.0, this module compares the total γ-ray flux to a joint-likelihood analysis of fifteen dwarf spheroidal galaxies (dSphs) analyzed by the Fermi-LAT collaboration. DarkFlux v1.0 automatically provides data tables and can plot the output of these three modules. In this manual, we briefly motivate this indirect-detection computer tool and review the essential DM physics. We then describe the several modules of DarkFlux in greater detail. Finally, we show how to install and run DarkFlux and provide two worked examples demonstrating its capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗

Microstructural study and densification analysis of hot work tool steel matrix composites reinforced with TiB{sub 2} particles

Hot work tool steels are characterized by good toughness and high hot hardness but are less wear resistant than other tooling materials, such as high speed steel. Metal matrix composites show improved tribological behavior, but not much work has been done in the field of hot work tool steels. In this paper TiB{sub 2}-reinforced hot work tool steel matrix composites were produced by spark plasma sintering (SPS). Mechanical alloying (MA) was proposed as a suited process to improve the composite microstructure. Density measurements and microstructure confirmed that MA promotes sintering and produces a fine and homogeneous dispersion of reinforcing particles. X-ray diffraction patterns of the sintered composites highlighted the formation of equilibrium Fe{sub 2}B and TiC, as predicted by thermodynamic calculations using Thermo-Calc® software. Scanning electron microscopy as well as scanning Kelvin probe force microscopy highlighted the reaction of the steel matrix with TiB{sub 2} particles, showing the formation of a reaction layer at the TiB{sub 2}-steel interface. Phase investigations pointed out that TiB{sub 2} is not chemically stable in steel matrix because of the presence of carbon even during short time SPS. - Highlights: • TiB{sub 2} reinforced steel matrix composites were produced by spark plasma sintering. • TiB{sub 2} was successfully dispersed in the steel matrix by mechanical alloying. • Steel and TiB{sub 2} react during sintering forming equilibrium Fe{sub 2}B and TiC. • The new phases were investigated by means of AFM, Volta potential and XRD analyses.

36 MATERIALS SCIENCE↗

Surface prediction and measurement for modulated tool path (MTP) turning

Here, this paper describes a time-domain simulation for predicting surface finish in modulated tool path (MTP) turning, which uses sinusoidal axis motions in the feed direction to produce discontinuous chips for ductile workpiece materials. The simulation includes: the low frequency and low amplitude tool oscillation in the feed direction; the time-varying chip thickness, cutting force, and tool displacement; and the plastic side flow effect used to calibrate the effective tool nose radius. Comparisons between predicted and measured surface profiles are presented for turning a 6061-T6 aluminum cylinder as a function of the MTP oscillation frequency and amplitude with discontinuous chip formation.

42 ENGINEERING↗

Effect of tool design and pass strategy on defect elimination and uniform, enhanced tensile properties of friction stir processed high-pressure die-cast A380 alloy

This work reports implementation of friction stir processing (FSP) to locally modify microstructure and create a defect-free processing zone with the aid of different tool designs and altering the passing strategy for two different process parameter combinations. Here, FSP is applied on high pressure die-cast (HPDC) A380 alloy, a widely used Al-Si alloy fabricated in the die casting sector for automotive and aerospace applications. However, the presence of gas and shrinkage porosity, brittle needle-shaped Fe-containing ß-FeSiAl 5 intermetallic compounds, Al-dendrites, coarse and acicular silicon particles, and large second-phase particulates have a detrimental influence on the uniformity of tensile properties across the thickness direction of an HPDC plate. FSP is able to eliminate porosity, refine microstructure and improve tensile properties. An FSP tool design and a passing strategy are identified for the best microstructure consolidation and uniform enhanced tensile properties. This study noted the importance of tool features such as scroll design and flats on tool pin and multiple pass orientation strategy to find best combination of defect-free refined microstructure and uniform tensile strength and ductility across the processing zone of HPDC Al alloys.

36 MATERIALS SCIENCE↗

An agent-based modeling tool supporting bioenergy and bio-product community communication regarding cellulosic bioeconomy development

The emergence of the cellulosic bioeconomy requires not only adequate technological, economic, and policy advances, but also effective communication and coordination among the multiple stakeholders in the bioeconomy community. Aiming to facilitate stakeholder communication and collaboration for cellulosic bioeconomy growth, an agent-based model is developed as a community communication tool in this study. The tool simulates the behaviors and interactions of key stakeholders, as well as the responses and interactions between the stakeholders and biophysical, socioeconomic, and environmental conditions. The agent behavior rules are developed and validated based on behavior and economic theories and information attained from a stakeholder focus group study and a land use survey. A pilot study in a Central Illinois watershed shows stakeholder synergies, i.e., positive feedback loops across multiple stakeholders. The modeling tool's role in facilitating community communication is demonstrated via the focus group study. A comparison of policy scenarios suggests that the cellulosic bioeconomy development is fastest under a portfolio of policies combining the views of the multiple stakeholders. Critically, subsidy for small-scale bio-facilities is essential as it rapidly initializes an early market for cellulosic feedstocks and the adoption of Miscanthus. As a result, the communication tool is applied to bringing stakeholders and researchers together to develop shared visions, assess barriers, and explore solution portfolios to initialize and speed up the regional cellulosic bioeconomy.

09 BIOMASS FUELS↗

PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data

Mass spectrometry is broadly employed to study complex molecular mechanisms in various biological and environmental fields, enabling 'omics' research such as proteomics, metabolomics, and lipidomics. As study cohorts grow larger and more complex with dozens to hundreds of samples, the need for robust quality control (QC) measures through automated software tools becomes paramount to ensure the integrity, high quality, and validity of scientific conclusions from downstream analyses and minimize the waste of resources. Since existing QC tools are mostly dedicated to proteomics, automated solutions supporting metabolomics are needed. To address this need, we developed the software PeakQC, a tool for automated QC of MS data that is independent of omics molecular types (i.e., omics-agnostic). It allows automated extraction and inspection of peak metrics of precursor ions (e.g., errors in mass, retention time, arrival time) and supports various instrumentations and acquisition types, from infusion experiments or using liquid chromatography and/or ion mobility spectrometry front-end separations and with/without fragmentation spectra from data-dependent or independent acquisition analyses. Diagnostic plots for fragmentation spectra are also generated. Here, in this paper, we describe and illustrate PeakQC’s functionalities using different representative data sets, demonstrating its utility as a valuable tool for enhancing the quality and reliability of omics mass spectrometry analyses.

47 OTHER INSTRUMENTATION↗

Using online tools at the Bovine Genome Database to manually annotate genes in the new reference genome

With the availability of a new highly contiguous Bos taurus reference genome assembly (ARS-UCD1.2), it is the opportune time to upgrade the bovine gene set by seeking input from researchers. Furthermore, advances in graphical genome annotation tools now make it possible for researchers to leverage sequence data generated with the latest technologies to collaboratively curate genes. For many years the Bovine Genome Database (BGD) has provided tools such as the APOLLO genome annotation editor to support manual bovine gene curation. The goal of this paper is to explain the reasoning behind the decisions made in the manual gene curation process while providing examples using the existing BGD tools. We will describe the sources of gene annotation evidence provided at the BGD, including RNAseq and Iso-Seq data. We will also explain how to interpret various data visualizations when curating gene models, and will demonstrate the value of manual gene annotation. The process described here can be applied to manual gene curation for other species with similar tools. With a better understanding of manual gene annotation, researchers will be encouraged to edit gene models and contribute to the enhancement of livestock gene sets.

59 BASIC BIOLOGICAL SCIENCES↗

Approaches to genetic tool development for rapid domestication of non-model microorganisms

Abstract Non-model microorganisms often possess complex phenotypes that could be important for the future of biofuel and chemical production. They have received significant interest the last several years, but advancement is still slow due to the lack of a robust genetic toolbox in most organisms. Typically, “domestication” of a new non-model microorganism has been done on an ad hoc basis, and historically, it can take years to develop transformation and basic genetic tools. Here, we review the barriers and solutions to rapid development of genetic transformation tools in new hosts, with a major focus on Restriction-Modification systems, which are a well-known and significant barrier to efficient transformation. We further explore the tools and approaches used for efficient gene deletion, DNA insertion, and heterologous gene expression. Finally, more advanced and high-throughput tools are now being developed in diverse non-model microbes, paving the way for rapid and multiplexed genome engineering for biotechnology.

09 BIOMASS FUELS↗

An ensemble model of QSAR tools for regulatory risk assessment

Quantitative structure activity relationships (QSARs) are theoretical models that relate a quantitative measure of chemical structure to a physical property or a biological effect. QSAR predictions can be used for chemical risk assessment for protection of human and environmental health, which makes them interesting to regulators, especially in the absence of experimental data. For compatibility with regulatory use, QSAR models should be transparent, reproducible and optimized to minimize the number of false negatives. In silico QSAR tools are gaining wide acceptance as a faster alternative to otherwise time-consuming clinical and animal testing methods. However, different QSAR tools often make conflicting predictions for a given chemical and may also vary in their predictive performance across different chemical datasets. In a regulatory context, conflicting predictions raise interpretation, validation and adequacy concerns. To address these concerns, ensemble learning techniques in the machine learning paradigm can be used to integrate predictions from multiple tools. By leveraging various underlying QSAR algorithms and training datasets, the resulting consensus prediction should yield better overall predictive ability. We present a novel ensemble QSAR model using Bayesian classification. The model allows for varying a cut-off parameter that allows for a selection in the desirable trade-off between model sensitivity and specificity. The predictive performance of the ensemble model is compared with four in silico tools (Toxtree, Lazar, OECD Toolbox, and Danish QSAR) to predict carcinogenicity for a dataset of air toxins (332 chemicals) and a subset of the gold carcinogenic potency database (480 chemicals). Leave-one-out cross validation results show that the ensemble model achieves the best trade-off between sensitivity and specificity (accuracy: 83.8 % and 80.4 %, and balanced accuracy: 80.6 % and 80.8 %) and highest inter-rater agreement [kappa (κ): 0.63 and 0.62] for both the datasets. The ROC curves demonstrate the utility of the cut-off feature in the predictive ability of the ensemble model. In conclusion, this feature provides an additional control to the regulators in grading a chemical based on the severity of the toxic endpoint under study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MURMoT. Design and Application of Microbial Uranium Reduction Monitoring Tools

Uranium (U) contamination in the subsurface is a major remediation challenge at many DOE sites. Traditional site remedies present enormous costs to DOE; hence, enhanced bioremediation technologies (i.e., biostimulation and bioaugmentation) combined with monitoring efforts are being considered as cost-effective corrective actions to address subsurface contamination. This research effort improved understanding of the microbial U reduction process and developed new tools for monitoring microbial activities. Application of these tools will promote science-based site management decisions that achieve contaminant detoxification, plume control, and long-term stewardship in the most efficient manner. The overarching hypothesis was that the design, validation and application of a suite of new molecular and biogeochemical tools advance process understanding, and improve environmental monitoring regimes to assess and predict in situ U immobilization. Accomplishments: This project (i) advanced nucleic acid-based approaches to elucidate the presence, abundance, dynamics, spatial distribution, and activity of metal- and radionuclide-detoxifying bacteria; (ii) developed proteomics workflows for detection of metal reduction biomarker proteins in laboratory cultures and contaminated site groundwater; (iii) developed and demonstrated the utility of U isotopic fractionation using high precision mass spectrometry to quantify U(VI) reduction for a range of reduction mechanisms and environmental conditions; and (iv) validated the new tools using field samples from U-contaminated IFRC sites, and demonstrated their prognostic and diagnostic capabilities in guiding decision making for environmental remediation and long-term site stewardship.

54 ENVIRONMENTAL SCIENCES↗

Additive Manufacturing of Tooling for Refrigeration Cabinet Foaming Processes

The primary objective of this project was to leverage the Big Area Additive Manufacturing (BAAM) process and materials into a long term, quick change tooling concept to drastically reduce product lead and development timelines and costs. Current refrigeration foam molds are complicated to manufacture involving casting several aluminum parts in an approximate shape, machining components of the molds and post fitting and shimming of the parts in an articulated fixture. The total process timeline can take over 6 months. The foaming process is slower than required for production, therefore multiple fixtures, 10 to 27, are required per refrigerator model. Molds are particular to a specific product configuration making mixed model assembly challenging for sequencing, mold changes or auto changeover features. The initial goal was to create a tool leveraging the ORNL materials and additive process to build a tool in 4 to 6 weeks or less. A secondary goal was to create common fixture cores and provide lightweight fixture sections that could be revised in a very short time to increase equipment flexibility reduce lead times, lower the barriers to first production trials, and reduce tooling costs.

3d Printing↗

Microgrid Analysis Tools Summary

The over-arching goal of the Alaska Microgrid Partnership is to reduce the use of total imported fuel into communities to secure all energy services by at least 50% in Alaska's remote microgrids without increasing system life cycle costs while also improving overall system reliability, security, and resilience. One goal of the Alaska Microgrid Partnership is to investigate whether a combination of energy efficiency and high-contribution (from renewable energy) power systems can reduce total imported energy usage by 50% while reducing life cycle costs and improving reliability and resiliency. This presentation provides an overview of the following four renewable energy optimization tools. Information is from respective tool websites, tool developers, and author experience. Distributed Energy Resources Customer Adoption Model (DER-CAM) Microgrid Design Toolkit (MDT) Renewable Energy Optimization (REopt) Tool Hybrid Optimization Model for Electric Renewables (HOMER).

17 WIND ENERGY↗

SoK: A Framework for and Analysis of Software Bill of Materials Tools

Modern software development has gradually become more complex, leveraging available open-source software and third party components. This practice has raised questions about the provenance, licensing, versioning and compliance of reused code and its dependencies. Furthermore, it is par ticularly important to review such code fragments and third party components for known-vulnerabilities before they are included in a software product. A Software Bill of Materials (SBoM) is a mechanism to achieve such an analysis, provid ing transparency and visibility into a software product to both the software developer and its respective consumer. An SBoM lists information and details about all the elements constituting a piece of software and can, therefore, be used to evaluate associated security risk. While the concept of SBoMs is growing in popularity, it is still fairly new to many organizations, causing them to potentially struggle with pro ducing and processing SBoMs and limiting their widespread adoption. In this work, we delve into the area of SBoMs and present the state-of-the-art SBoM tools, creating a framework for analysis and categorizing them based on a diverse set of features and functionalities. We are the first to provide a detailed analysis of 83 open-source SBoM tools along with a perspective on how a potential SBoM user can select a tool based on their specific requirements. Our work aims to help promote understanding of this domain, thereby encouraging and furthering its overall adoption. We additionally seek to pave a path for future work in this area by providing recommendations to tool developers and users, researchers, and standardizing organizations.

99 GENERAL AND MISCELLANEOUS↗

Ultrafast Sharpening of a Hard-Alloy Tool

The sharpening of hard-alloy cutting tools affects their life and reliability and the quality of the machined surface. In the case of imported tools for high-precision machining, the rounding radius of the cutting edge after sharpening is 10–15 µm. That permits machining with chip thickness no less than 20–30 µm. This limit is often critical, since the machining precision of some important components is 3–5 µm. In addition, such sharpening shortens the potential tool life. If sharpening is improved so that the rounding radius of the cutting edge is 3–5 µm, the machining precision is enhanced and tool life is extended. That improves machining [2].

42 ENGINEERING↗

Controlling the State of Machine Tools

Globally, manufacturers make great efforts to maintain the performance of industrial equipment. Developers and researchers are interested in automated approaches to maintaining the performance of equipment, especially at enterprises with high degrees of computerization and comprehensive information systems. In the present work, a new approach is outlined: an autonomous control system for maintaining the condition of metal-cutting machines. This approach is based on prior work in the field and permits maintenance on the basis of autonomous control of the state of machine tools. The structure of a system with the following generalized control functions is presented: decision making; and the issuing of commands on the basis of built-in resources. The formulation of control decisions employs the theory of fuzzy sets and fuzzy logic. By means of the ANFIS fuzzy network system, the autonomy of state control of the machine tool may be assessed. Criticality assessment of the condition of machine tools and their components is important in making decisions as to the setup of systems controlling the condition of equipment at enterprises, with assessment of their efficiency. In the monitoring subsystem, provision is made for assessment of the diagnostic results, prediction, and the generation of control decisions so as to prevent disruptions of machine-tool operation.

42 ENGINEERING↗

Preventing Faults in Machine Tools for Critical Cooperative and Distributed Industrial Productions

A critically important high-tech industrial enterprise forms part of a territorially distributed cooperative production system. Precise optimization of management decisions regarding fault prevention in its stock of machine tools is very important. Up-to-date tools for management decisions must be used for that purpose. Those tools must support the basic management functions and include software for high-level mathematical models of machine-tool operation (models of the state of the equipment and a model of its use in the course of production) and a model of the economic potential of the enterprises.

42 ENGINEERING↗

Agrivoltaic Decision Tools for Perennial and Field Crop Farmers

This article describes a series of spreadsheet-based tools to help farmers estimate costs, revenues, and yields from agricultural production under different configurations of agrivoltaic installations for field and perennial crops. Crop-specific log books allow farmers to project changes in activity-level costs from the field due to agrivoltaic installations. The whole-farm tool helps farmers aggregate activity-level net returns up to the farm level to calculate projections of trade-offs between crop production with or without agrivoltaic installations. We present tools for lettuce and cranberries, but the tools are comprehensive and inclusive and so can be modified for other perennial and field crops.

14 SOLAR ENERGY↗

An Evaluation of Operational Airspace Sectorization Integrated System (OASIS) Advisory Tool

In January 2013, a human-in-the-loop evaluation of the Operational Airspace Sectorization Integrated System (OASIS) was conducted in the Airspace Operations Laboratory of the Human Systems Integration Division (Code TH) in conjunction with the Aviation Systems Division (Code AF). The development of OASIS is a major activity of the Dynamic Airspace Configuration (DAC) research focus area within the Aeronautics Research Mission Directorate (ARMD) Airspace Systems Program. OASIS is an advisory tool to assist Federal Aviation Administration (FAA) En Route Area Supervisors in their planning of sector combinedecombine operations as well as opening closing of Data-side (D-side) control positions. These advisory solutions are tailored to the predicted traffic demand over the next few hours. During the experiment, eight retired FAA personnel served as participants for a part-task evaluation of OASIS functionality, covering the user interface as well as the underlying algorithm. Participants gave positive feedback on both the user interface and the algorithm solutions for airspace configuration, including an excellent average rating of 94 on the tool usability scales. They also suggested various enhancements to the OASIS tool, which will be incorporated into the next tool development cycle for the full-scale human-in-the-loop evaluation to be conducted later this year.

decision support tools↗