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This implementation of a Physics Guided Neural Network (PHYGNN) augments a traditional neural network loss function with a generic term that can be used to guide the neural network to learn physical or theoretical constraints.
XPlacer Machine Learning Guided Data Placement uses machine learning model to assist programmers to select the data placement advises for application running on HPC system with Nvidia GPUs. XPlacer Machine Learning Guided Data Placement consists three components: (1) 4 revised benchmarks from Rodinia benchmarks; (2) compiler script and execution script to generate variants, and collect training data for the machine learning model; (3) the scripts to post-process the collected data and generate the machine leaning model.
SAND2021-15515 O The Vulnerability Research Development Program (VRDP) Guide is a training program developed to help general purpose computer science staff become independently capable vulnerability researchers. VRDP Guide is both a course description and curriculum for the program. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Background: Surgical resection with negative margins is the foundation of extremity sarcoma management. Failure to achieve negative surgical margins can result in local recurrence (LR), a potentially devastating complication. Indocyanine green (ICG) is a US FDA-approved fluorophore previously used to guide carcinoma resections. We investigated the potential of ICG as an intraoperative guide during experimental sarcoma resection. Methods: Fifty 6-week-old immunocompetent Balb/c female mice received left proximal tibia paraphyseal injections of 5 × 10{sup 5} K7M2 murine osteosarcoma cells. Animals were separated into two groups (n = 25 each): (1) ICG-assisted surgical resection; and (2) no ICG-assisted resection. Resections were performed 4 weeks after primary tumor engraftment. All animals received 7.5 ug ICG via retro-orbital injection 12 h prior to surgery. ICG fluorescence measurements and clinical evaluations were performed 4 weeks after resection to detect LR. Results: Eleven of 25 animals from each group developed gross tumors. Four weeks after resection, group 1 had 0/11 tumor recurrences, while group 2 had recurrences in 9/11 (81.8%) experimental mice (p < 0.0002) (Fig. 2). There was a 100% NPV in group 1, and no tumor recurrence with fluorescence-free margins after the primary surgery. Group 2 had a 100% positive predictive value for the development of an LR if any fluorescent signal was present at the surgical margin after resection. Conclusion: Intraoperative ICG guidance led to reliably negative surgical margins and a diminished LR rate. Given the benign safety profile of ICG and its prior clinical success, these results could be immediately translatable to the clinical realm.
Spatially and temporally dependent optical aberrations induced by the inhomogeneous refractive index of live samples limit the resolution of live dynamic imaging. We introduce an adaptive optical microscope with a direct wavefront sensing method using a Shack-Hartmann wavefront sensor and fluorescent protein guide-stars for live imaging. The results of imaging Drosophila embryos demonstrate its ability to correct aberrations and achieve near diffraction limited images of medial sections of large Drosophila embryos. GFP-polo labeled centrosomes can be observed clearly after correction but cannot be observed before correction. Four dimensional time lapse images are achieved with the correction of dynamic aberrations. These studies also demonstrate that the GFP-tagged centrosome proteins, Polo and Cnn, serve as excellent biological guide-stars for adaptive optics based microscopy.
Waveguide superlattices with a subwavelength pitch and low crosstalk can significantly increase the waveguide integration density and are beneficial for many chip-scale applications. Bending of such high-density waveguide superlattices is necessary for flexible signal routing. However, tight bending tends to induce high crosstalk between guided modes, as witnessed in multimode waveguide bends. Here we explore the mechanisms of light guiding and coupling in a subwavelength-pitch waveguide superlattice bend and analyze how bending further modifies the already “renormalized” parameters of superlattice modes via various physical effects. Particularly, bending can skew the phase mismatch in a waveguide superlattice, sometimes producing a near phase-matching condition and causing salient crosstalk spikes among non-first-nearest neighbors. Interestingly, a waveguide superlattice with less pristine phase mismatch may be more robust against such skew of phase mismatch and can suppress crosstalk spikes by ~10 dB. Bending with 5–15 μm radii and subwavelength pitches has been demonstrated with crosstalk lower than -19.5 dB. The scaling of the footprint of waveguide superlattice bending is analyzed, and significant footprint reduction can be achieved for chip-scale applications. The rationale for footprint reduction of superlattice bending under crosstalk constraint differs markedly from that of a single waveguide bend.
The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding its potential for understanding the biology and evolution of the full spectrum of biodiversity. The increasing diversity of sequencing technologies, assays, and de novo assembly algorithms have augmented the complexity of de novo genome sequencing projects in nonmodel organisms. To reduce the costs and challenges in de novo genome sequencing projects and streamline their experimental design and analysis, we developed iWGS (in silico Whole Genome Sequencer and Analyzer), an automated pipeline for guiding the choice of appropriate sequencing strategy and assembly protocols. iWGS seamlessly integrates the four key steps of a de novo genome sequencing project: data generation (through simulation), data quality control, de novo assembly, and assembly evaluation and validation. The last three steps can also be applied to the analysis of real data. iWGS is designed to enable the user to have great flexibility in testing the range of experimental designs available for genome sequencing projects, and supports all major sequencing technologies and popular assembly tools. Three case studies illustrate how iWGS can guide the design of de novo genome sequencing projects, and evaluate the performance of a wide variety of user-specified sequencing strategies and assembly protocols on genomes of differing architectures. iWGS, along with a detailed documentation, is freely available at https://github.com/zhouxiaofan1983/iWGS.
NOTE: The manuscript associated with this data package is currently in review. The data/scripts may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final scripts and additional metadata. This data package is associated with the publication “Revisiting controls on hyporheic respiration with knowledge-guided machine learning at continental scale” submitted to Environmental Science & Technology (Zheng et al. 2026). The project combines mechanistic process modeling with knowledge-guided machine learning (KGML) to evaluate how organic matter chemistry, microbial biomass, and physical substrate accessibility regulate realized respiration rates across river corridors. All data used in this paper have been previously published and can be accessed at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719 (Goldman et al., 2020). This data package contains 3 R-markdown (Rmd) preprocessing scripts for the previously published data and subsequent modelling workflows. The full workflow with input and output data can be found in the associated GitHub repository at https://github.com/jianqiuz/KGML-WHONDRS.
This is an addendum to the Sierra/SolidMechanics 4.22 User's Guide to document additional capabilities that are available for use in the Presto{_}ITAR code that are not available for use in the standard version of Sierra/SolidMechanics (Sierra/SM). Presto{_}ITAR is an enhanced version of Sierra/SM that provides capabilities that make it regulated under the U.S. Department of State's International Traffic in Arms Regulations (ITAR) export-control rules. This code is part of the Vivace product, and is only distributed to entities that comply with ITAR regulations. The enhancements primarily focus on material models that include an energy-dependent pressure response, appropriate for very large deformations and strain rates. Since this is an addendum to the standard Sierra/SolidMechanics User's Guide, please refer to that document first for general descriptions of code capability and use. This addendum documents material models and element features that support energy-dependent material models.
This guide is organized around three sponsorship models: utility-sponsored projects, projects sponsored by special purpose entities - businesses formed for the purpose of producing community solar power, and non-profit sponsored projects. The guide addresses issues common to all project models, as well as issues unique to each model.
This STOMP (Subsurface Transport Over Multiple Phases) guide document describes the theory, use, and application of the STOMP-CO2 and STOMP-CO2e operational modes. These operational modes of the STOMP simulator are configured to solve problems involving the sequestration of CO2 in geologic saline reservoirs. STOMP-CO2 is the isothermal version and STOMP-CO2e is the nonisothermal version. These core operational modes solve the governing conservation equations for component flow and transport through geologic media; where, the STOMP-CO2 components are water, CO2 and salt and the STOMP-CO2e operational mode also includes an energy conservation equation. Geochemistry can be included in the problem solution via the ECKEChem (Equilibrium-Conservation-Kinetic-Equation Chemistry) module, and geomechanics via the EPRMech (Elastic-Plastic-Rock Mechanics) module. This addendum is designed to provide the new user with a full guide for the core capabilities of the STOMP-CO2 and -CO2e simulators, and to provide the experienced user with a quick reference on implementing features. Several benchmark problems are provided in this addendum, which serve as starting points for developing inputs for more complex problems and as demonstrations of the simulator’s capabilities.
This how-to guide explains the issues and concerns with conventional ventilated crawlspaces and provides prescriptive measures for improvements that will create healthier and more durable spaces. The methods described in this guide are not the only acceptable ways to treat a crawlspace but represent a proven strategy that works in many areas of the United States. The designs discussed in thisguide may or may not meet the local building codes and as such will need to be researched before beginning the project.
This report was prepared by PNNL for DOE's Building America program and is intended as a guide that energy performance contractors can share with homeowners to describe various insulation options for improving the energy performance and comfort of existing homes. The report provides descriptions of many common insulation types, including their advantages and disadvantages, R-values, characteristics, and typical uses. The report also describes potentially hazardous products such as asbestos and formaldehyde and safety issues when conducting energy-efficient upgrades including radon. The guide is available for download at the DOE Building America website, www.buildingamerica.gov.
The Portable Isotopic Neutron Spectroscopy—PINS, for short—system identifies the chemicals inside munitions and containers without opening them, a decided safety advantage if the fill chemical is a hazardous substance like a chemical warfare agent or an explosive. The PINS Spectrum Identification Guide is intended as a reference for technical professionals responsible for the interpretation of PINS gamma-ray spectra. The guide is divided into two parts. The three chapters that constitute Part I cover the science and technology of PINS. Neutron activation analysis is the focus of Chapter 1. Chapter 2 explores PINS hardware, software, and related operational issues. Gamma-ray spectral analysis basics are introduced in Chapter 3. The six chapters of Part II cover the identification of PINS spectra in detail. Like the PINS decision tree logic, these chapters are organized by chemical element: phosphorus-based chemicals, chlorine-based chemicals, etc. These descriptions of hazardous, toxic, and/or explosive chemicals conclude with a chapter on the identification of the inert chemicals, e.g. sand, used to fill practice munitions.
Guiding center simulations are an important means of predicting the effect of resistive and ideal magnetohydrodynamic instabilities on particle distributions in toroidal magnetically confined thermonuclear fusion research devices. Because saturated instabilities typically have amplitudes of δ B/B of a few times 10 -4 numerical accuracy is of concern in discovering the effect of mode particle resonances. We develop a means of following guiding center orbits which is greatly superior to the methods currently in use. In the presence of ripple or time dependent magnetic perturbations both energy and canonical momentum are conserved to better than one part in 10 14 , and the relation between changes in canonical momentum and energy is also conserved to very high order.
Today's fleets are increasingly interested in medium-duty and heavy-duty vehicles that use alternative fuels or advanced technologies that can help reduce operating costs, meet emissions requirements, improve fleet sustainability, and support U.S. energy independence. Vehicle and engine manufacturers are responding to this interest with a wide range of options across a steadily growing number ofvehicle applications. This guide provides an overview of alternative fuel power systems?including engines, microturbines, electric motors, and fuel cells?and hybrid propulsion systems. The guide also offers a list of individual medium- and heavy-duty vehicle models listed by application, along with associated manufacturer contact information, fuel type(s), power source(s), and relatedinformation.
The BioWatch Sample Management System is software developed by Los Alamos National Laboratory to support the Department of Homeland Security BioWatch program. Field Operations Supervisors use the software to record, track, and manage data for the BioWatch sample collection process. This includes installing the software, creating and updating databases, assigning user IDs and passwords, editing and customizing reports, correcting data errors, recovering lost data, and troubleshooting. The BioWatch SMS Field Operations Supervisor Guide provides procedures for each task a Field Operations Supervisor performs. The reference information in this guide includes appendices of error messages and solutions, terms used interchangeably, and safety warnings along with a glossary, an index, and a list of suggested reference documents.
The BioWatch Sample Management System is software developed by Los Alamos National Laboratory to support the Department of Homeland Security BioWatch program. Field Operators use the software to keep track of samples and to provide information on the sample management process to other users and software programs within BioWatch. The information tracked about a sample includes the date and time the filter media is assembled in a filter holder, deployed to the field, placed in and removed from a collector, and received from the field, and identifies who performs each task. Field Operators can also use the software to prepare and print forms to document the chain-of-custody transfer of the samples. The BioWatch SMS Field Operator Guide provides easy-to-understand procedures for each task a Field Operator performs. This guide gives basic information about using the computer and other equipment, instructions about checking and editing data, and provides reference information, including appendices of error messages and solutions, words used interchangeably, and safety warnings plus a glossary and an index.