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Beam Dynamics simulations for ERDC project -- SRF linac for industrial use

Compact conductively cooled SRF industrial linacs can provide unique parameters of the electron beam for industrial applications. (up to 10MeV, 1MW). For ERDC project we designed normal conducting RF injector with thermal RF gridded gun integrated in first cell of multi-cell cavities. For design of the RF gun we used MICHELLE software to simulate and optimize parameters of the beam. Output file was converted to ASTRA format and most beam dynamic simulations in multi-cell normal conducting cavity and cryomodule were performed by using ASTRA software. For cross-checking we compare results of MICHELLE and AS-TRA in first few cells. At the end of injector beam reach ~250keV energy which allow to trap bunch in acceleration regime without losses in TESLA like 1.3 GHz cavity. Short solenoid at the end of injector allow to regulate transverse beam size in cryomodule to match beam to extraction system and also reduce charge losses in accelerator.

43 PARTICLE ACCELERATORS↗

Size-resolved ice nucleating particle (INP) concentrations from the MOSAiC campaign

Sample collection: Ground-based immersion mode ice nucleation measurements were conducted on samples collected at the U.S. DOE ARM AMF2 onboard the R/V Polarstern P-deck during MOSAiC from 23 Oct 2019 to 01 Oct 2020. Samples were collected using a Davis Rotating-drum Unit for Monitoring (DRUM; DRUMAir, LLC) cascading impactor in 4 stages (i.e., size bins). Instrument information on the model used, the DA400, can be found at the DRUMAir website (http://www.drumair.com/). Stages A, B, C, and D had particle size cuts at 2.96, 1.21, 0.34, and 0.15 &micro;m in particle diameter, respectively. Strips of sample substrate (PFA, perfluoroalkoxy; McMaster) were adhered to each disc in each stage and coated with petrolatum to enable particles to stick on impact. The discs move slowly over time, such that aerosol loading is streaked onto the PFA. Every 24 hours, a blank is created on the PFA to separate daily samples. During MOSAiC, the pump typically pulled 20 &ndash; 35 lpm (average of 32 lpm) at the inlet with all the discs in place in each stage. Daily samples were collected for each of the four stages, equaling 28,800 &ndash; 50,400 total L of air (average of 46,080 L total L of air) per sample. Discs rotated for approximately 24 days before the sampling per strip was complete and changed to a new disc. Discs were stored frozen after collection. Sample preparation for analysis: Following collection and transport from MOSAiC to the Kreidenweis/DeMott laboratory, care of PI Creamean, in Fort Collins, CO, strips were removed from the discs and cut up to separate daily samples. Each daily portion of the strip was stored in separate sterile 15-mL centrifuge tubes and stored in a standard commercial freezer until analysis (approximately 4 &ndash; 12 months after collection). Sample analysis: Drop freezing assays (DFAs) were conducted on one daily sample set every 3 &ndash; 4 days of the study for all four stages using the Colorado State University (CSU) cold plate (CP). Sample set days were chosen to cover the entire year of MOSAiC and avoiding days where the AOS purge system was activated. Immediately after removal from the freezer, 2 mL of 0.1-&micro;m filtered deionized water was added with a single-use sterile syringe directly to the tubes, then mixed using a vortex mixer for at least 30 minutes at 500 rpm to resuspend particles from the PFA into the deionized water. Following sample preparation, another single-use syringe was used to create 100 aliquots on a 3-inch diameter copper plate, then covered with a transparent plastic dome. The drops were approximately the same volume (2.5 &micro;L each), though careful inspection. The plate was cooled at approximately 3 &ndash; 10 K min-1 from room temperature until all drops froze on the plate. Temperature was measured by an Omega thermocouple probes and meter. Drop freezing was visually detected but recorded through monitoring software to provide the time frozen, channel of the meter used, temperature, and cooling rate for each drop. Not all 100 drops were always detected; the total number of rows in each data file equals the number of drops recorded, which typically was > 80 %. Each sample was tested three times (i.e., a new set of 100 drops was created for each test). Data provided are files containing these parameters. From the freezing temperatures recorded, the fraction frozen was and INP concentrations were calculated per L of air using the equation from Vali (1971): [INPs] = &minus;(ln(f)/Valiquot)*(Vsuspension/Vair) where f is the proportion of droplets not frozen, Valiquot is the volume of each aliquot (i.e., 2.5e-6 L), Vsuspension is the volume of the suspension (i.e., 0.002 L), and Vair is the volume of air per sample (i.e., 36000 L). Data usage guidance: There are three files included with this dataset: (1) dumcp_inp_concentrations.csv which includes cumulative INP concentrations binned every 0.5 &deg;C from 0 to &ndash;30 &deg;C for all samples and size ranges (i.e., DRUM stages) processed via DFA using the CSU CP; (2) dumcp_inp_standard_deviation.csv which includes the standard deviations for all samples and temperatures in dumcp_inp_concentrations.csv; and (3) dumcp_blank_concentrations_standard_deviation.csv which includes the INP concentrations and standard deviations for the deionized water and PFA blanks binned every 0.5 &deg;C from 0 to &ndash;30 &deg;C. The first column in each file represents the freezing temperature in &deg;C binned every 0.5 &deg;C from 0 to &ndash;30 &deg;C (first cell in this column = header = &ldquo;temp&rdquo;). The second column in each file represents the standard deviation of each temperature bin in &deg;C (first cell in this column = header = &ldquo;temperr&rdquo;). For file (1) dumcp_inp_concentrations.csv, the remaining columns indicate the INP concentrations per L of air for each temperature bin. For each sample column, the header in the first row indicates the stage (i.e., size bin as &ldquo;A_&rdquo;, &ldquo;B_&rdquo;, &ldquo;C_&rdquo;, or &ldquo;D_&rdquo;) and date (&ldquo;_yyyymmdd) of collection. For file (2) dumcp_inp_standard_deviation.csv, the remaining columns indicate the INP concentration standard deviation per L of air for each temperature bin. For each sample column, the header in the first row indicates the stage (i.e., size bin as &ldquo;A_&rdquo;, &ldquo;B_&rdquo;, &ldquo;C_&rdquo;, or &ldquo;D_&rdquo;) and date (&ldquo;_yyyymmdd) of collection. For file (3) dumcp_blank_concentrations_standard_deviation.csv, the remaining columns indicate the INP concentrations and standard deviations for the deionized water blank (&ldquo;di_0.1&rdquo; and &ldquo;di_0.1sd&rdquo; for the concentrations and standard deviations, respectively) and PFA blank (&ldquo;pfa&rdquo; and &ldquo;pfasd&rdquo; for the concentrations and standard deviations, respectively). Please see Creamean et al. (2019a; 2018a; 2018b; 2019b) for additional details on DRUM sample collection and offline processing. For questions or help with data interpretation, contact Dr. Jessie Creamean (jessie.creamean@colostate.edu). References: Creamean, J. M., Mignani, C., Bukowiecki, N., and Conen, F.: Using spectra characteristics to identify ice nucleating particle populations during winter storms in the Alps, Atmos. Chem. Phys., 19, 8123&ndash;8140, 2019a. Creamean, J. M., Kirpes, R. M., Pratt, K. A., Spada, N. S., Maahn, M., de Boer, G., Schnell, R. C., and China, S.: Marine and terrestrial influences on ice nucleating particles during continuous springtime measurements in an Arctic oilfield location, Atmospheric Chemistry and Physics, 18, 18023-18042, 10.5194/acp-18-18023-2018, 2018a. Creamean, J. M., Primm, K. M., Tolbert, M. A., Hall, E. G., Wendell, J., Jordan, A., Sheridan, P. J., Smith, J., and Schnell, R. C.: HOVERCAT: A novel aerial system for evaluation of aerosol-cloud interactions, Atmospheric Measurement Techniques, 11, 3969-3985, 10.5194/amt-11-3969-2018, 2018b. Creamean, J. M., Cross, J. N., Pickart, R., McRaven, L., Lin, P., Pacini, A., Hanlon, R., Schmale, D. G., Ceniceros, J., Aydell, T., Colombi, N., Bolger, E., and DeMott, P. J.: Ice nucleating particles carried from below a phytoplankton bloom to the Arctic atmosphere, Geophys. Res. Lett., 46, 8572-8581, https://doi.org/10.1029/2019GL083039, 2019b. Vali, G.: Quantitative Evaluation of Experimental Results an the Heterogeneous Freezing Nucleation of Supercooled Liquids, Journal of the Atmospheric Sciences, 28, 402-409, 10.1175/1520-0469(1971)028<0402:qeoera>2.0.co;2, 1971.

4-stage DRUM aerosol collector (DA400),Ice nuclei,↗

Vegetation Warming Experiment: Landscape-scale digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2022

Images captured using a StarDot NetCam SC phenocamera looking east from the top of the Barrow Environmental Observatory (BEO) Sled Shed, Utqiaġvik, Alaska. The camera was installed to remotely monitor plant phenology across the site of the Brookhaven National Laboratory (BNL) TEST group's ZPW (Zero Power Warming) experiment (2017-2021) during the growing season of 2022. Images were recorded from late spring (18 May) through to mid fall (25 October). Snowmelt, vegetation growth and senescence, and snow accumulation were captured. Images were uploaded to the BNL FTP server every hour, at 10 minute intervals from 2022-07-01 until 2021-08-10, then hourly until the end of data collection on 2022-10-25. Images have been combined in *.tar.gz format (6 GB, 7367 jpg images). The data package includes a metadata document with example fields of view from each month of operation (*.pdf).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Outdoor Test Bed Performance of a Power Line Sensor Using a Real-Time Event Simulator

This report summarizes the design and application of an outdoor power line sensor testbed (OPLST) with a real-time simulator and power meter to compare a potential transformer (PT) and current transformer (CT) versus an advanced line-post sensor. The OPLST was created to validate advanced medium-voltage (20/34.5 kV) outdoor power line sensors used in electrical distribution systems. Electrical utilities have installed metering and relay-protection transformers like PTs and CTs for several decades. The PTs/CTs are iron core measurement transformers based on the electromagnetic induction principle and provide reliable data in normal grid operation. However, new outdoor power line sensors (OPLS) using other technologies like voltage divider, Rogowski coil and optical principles have become available and may have favorable performance and costs compared to PTs/CTs. Therefore, the importance of testing these technologies with the PT/CT, to compare the measured phase voltage/current at different power grid scenarios is crucial to understand the performance of these new OPLS. For this study a G&W Electric Model CVS-36-O power line sensor was chosen as the OPLS to test with voltage/current signals. An OPAL-RT Technologies Model OP4510 real-time simulator and Schweitzer Engineering Laboratories Model SEL-735 power meter were installed with the 20/34.5 kV OPLST to compare the measured transient events collected from an advanced OPLS and the PT/CT. This system is installed at the Distributed Energy Communications and Control (DECC) lab, Oak Ridge National Laboratory (ORNL). The simulator generated different power grid scenarios (electrical faults, capacitor bank operation, service restoration, etc.), and its analog-output signals were connected to the voltage/current amplifiers that feed the 20/34.5 kV aerial cable loop through the PT/CT devices. Additional PT/CT devices were also wired with the medium voltage aerial cable loop to measure the phase current/voltage signals and server as references. After each test, common format for transient data exchange (COMTRADE) files were collected from the SEL-735 power meter and used to compare the performance of the OPLS with the PT/CT. The behavior of analog signals, harmonic components, total harmonic distortion and crest factors were assessed and found favorable for the G&W sensor as compared to the reference PT/CT.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A fast Monte Carlo cell-by-cell simulation for radiobiological effects in targeted radionuclide therapy using pre-calculated single-particle track standard DNA damage data

Introduction: We developed a new method that drastically speeds up radiobiological Monte Carlo radiation-track-structure (MC-RTS) calculations on a cell-by-cell basis. Methods: The technique is based on random sampling and superposition of single-particle track (SPT) standard DNA damage (SDD) files from a “pre-calculated” data library, constructed using the RTS code TOPAS-nBio, with “time stamps” manually added to incorporate dose-rate effects. This time-stamped SDD file can then be input into MEDRAS, a mechanistic kinetic model that calculates various radiation-induced biological endpoints, such as DNA double-strand breaks (DSBs), misrepairs and chromosomal aberrations, and cell death. As a benchmark validation of the approach, we calculated the predicted energy-dependent DSB yield and the ratio of direct-to-total DNA damage, both of which agreed with published in vitro experimental data. We subsequently applied the method to perform a superfast cell-by-cell simulation of an experimental in vitro system consisting of neuroendocrine tumor cells uniformly incubated with 177 Lu. Results and discussion: The results for residual DSBs, both at 24 and 48 h post-irradiation, are in line with the published literature values. Our work serves as a proof-of-concept demonstration of the feasibility of a cost-effective “in silico clonogenic cell survival assay” for the computational design and development of radiopharmaceuticals and novel radiotherapy treatments more generally.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

CROCUS Tipping Bucket Rain Gauge Data from Argonne Deployable Mast Deployed at NEIU Carruthers Center for Inner City Studies (CCICS)

The Tipping Bucket Rain Gauge (TBRG) dataset contains data from a non-heated Met One 12-inch tipping bucket rain gauge that was mounted on the Argonne Deployable Mast (ADM). The ADM is a rapid deployable meteorological trailer that can be outfitted with instrumentation to measure urban heat island effects, urban flooding or urban flux measurements. During the urban flooding field campaign, the ADM was outfitted with multiple precipitation measurement systems, including the TBRG. This dataset contains one minute measurements for precipitation accumulation during the ADM's deployment at the Northeastern Illinois University (NEIU) Carruthers Center for Inner City Studies (CCICS) campus. These data are helpful for identifying periods of precipitation, leading to potential flooding. TBRGs can be used to validate optical rain gauge data and disdrometer data collected during the CROCUS urban flooding campaign. Data were collected at the CCICS building parking lot, located in the south side of Chicago, IL. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (ADM-ccics), instrument name (tbrg), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or act-doe.

1-minute Precipitation Accumulation↗

NEWTS USGS Produced Waters Case Studies

Case studies from the USGS Produced Waters Database. Includes OLI Studio and Geochemist's Workbench files. Original data from: Blondes, M. S., Gans, K. D., Engle, M. A., Kharaka, Y. K., Reidy, M. E., Saraswathula, V., Thordsen, J. J., Rowan, E. L., & Morrissey, E. A. (2019). U.S. Geological Survey National Produced Waters Geochemical Database v2.3 [Data set]. U.S. Geological Survey. https://doi.org/10.5066/F7J964W8

Case Studies↗

Thermodynamic assessment of the quaternary WTaCrV refractory high entropy alloy as a means to guide experimental approaches

The deployment of fusion energy poses challenges for materials in plasma facing components to withstand high temperatures and thermal gradients, particle implantation and neutron damage. The current material of choice is tungsten, although property degradation limits its consideration in future fusion reactors. Hence, materials with better resistance to harsh environments need to be developed for fusion energy to become a reality. High entropy alloys are being explored as potential candidates with some compositions showing good radiation resistance to defect cluster formation. One of these materials is the WTaCrV system, although only one composition has been tested under ion irradiation. In this work, we study the thermodynamic properties of the entire quaternary alloy composition range. Coupling first principles calculations, cluster expansion approaches, and Monte Carlo methods, we access the free energy functionals, short-range ordering as a function of temperature, and atomic configurations that can be compared to experimental observations. We use this data to inform experiments into compositions with higher propensity to form solid solutions, instead of phase separating. With this formalism we have developed thermodynamic database (TDB) files that can be used to plot quaternary phase diagrams.

Cluster Expansion↗

SU-E-T-253: Development of a GDPM Monte Carlo Based Quality Assurance Tool for Cyberknife

Purpose: To develop a 3D quality assurance (QA) tool for Cyberknife plans using a GPU-based Monte Carlo dose calculation package, gDPM. The developed QA tool will be used as a secondary check for Cyberknife treatment planning software (TPS) reported dose distributions. Methods: Phase space files of the 5, 7.5, 10, 15, and 60 mm iris cones were downloaded from IAEA phase-space database. From the 60mm iris cone phase space file, we were able to generate raw phase space files for all other cones using a particle rejection method. The particles in the raw phase space files were binned with respect to the radial position and energy for commissioning. During the commissioning process, gDPM calculated percent depth dose and off-center ratios which were compared to those measured in the Blue Phantom. The off-axis data was measured with an SAD setup at depths of 15, 50, 100, 200, and 300 mm. At the commissioning stage, an optimization problem was solved to adjust the binned particles weights to minimize the difference between the calculated and measured ones. Commissioning validations will be performed by measuring point dose data of patient specific plans delivered to water phantoms. With commissioned phase space files, 3D patient-specific dose distributions will be calculated and compared against TPS reported dose. Results: Beyond the initial buildup region, the root mean square difference between the calculated and measured percent depth dose differences was less than 0.5%. The full-width half-max data from the off-axis ratio calculations was found to be within 0.1 mm of the measured data. Conclusion: Our current work showed excellent agreement between the gDPM calculated dose and the measured data for all cone sizes and types for the Cyberknife system. Implementation of a fast and accurate QA tool for patient specific plans will be feasible with this tool.

60 APPLIED LIFE SCIENCES↗

WHOLESCALE: Coordinates of wells at San Emidio, Nevada

This dataset includes position coordinates and elevation information for wells at the WHOLESCALE San Emidio project location. Well positions in the attached file are characterized by UTM coordinates (Easting, Northing) in meters, and WHOLESCALE coordinates (Easting, Northing) relative in meters from a chosen reference point. The elevation of the top and bottom of open intervals within each well (representing locations of perforated or open-hole sections) are measured in meters (positive) above WGS84 geoid (mean sea level). The WHOLESCALE acronym stands for Water & Hole Observations Leverage Effective Stress Calculations and Lessen Expenses. The goal of the WHOLESCALE project is to simulate the spatial distribution and temporal evolution of stress in the geothermal system at San Emidio in Nevada, United States.

15 GEOTHERMAL ENERGY↗

ESS-DIVE Reporting Format for Location Metadata

The ESS-DIVE location metadata reporting format provides instructions and templates for reporting a minimum set of metadata for discrete point locations in geographic space represented by x, y, and z coordinates. This format was created based on a need for earth and environmental science researchers to more consistently provide metadata about locations where they conduct studies. To create the format, we incorporated elements from ESS-DIVE’s community reporting formats as well as 12 additional data standards or other data resources (e.g., databases, data systems, or repositories). In the template, we ask researchers to indicate unique locations using Location IDs and indicate hierarchies of locations through parent location IDs. We also provide additional optional fields for researchers to indicate how they measured the point location and the date and time that the location was first used as a research siteThis dataset contains support documentation for the reporting format (README.md and instructions.md), a terminology guide (guide.md), a crosswalk indicating how this reporting format relates to existing standards and data resources (Location_metadata_crosswalk.csv), a data dictionary (dd.csv), file-level metadata (flmd.csv), and the location metadata templates in both CSV (Location_metadata_template.csv) and Excel formats (Location_metadata_template.xlsx).

54 ENVIRONMENTAL SCIENCES↗

BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions

Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.

25 - ENERGY STORAGE↗

Constraining Bedrock Groundwater Residence Times in a Mountain System with Environmental Tracer Observations and Bayesian Uncertainty Quantification: Modeling and Data Package

Groundwater residence times provide fundamental descriptions of hydrologic dynamics and mixing processes in mountainous watersheds. Yet, few observational datasets that can constrain groundwater residence times over broad timescales are available in high elevation mountain systems. Here we present field observations from May 2021 of dissolved noble gases (He, Ne, Ar, Kr, and Xe), Chloroflourcarbons (CFCs), Sulfurhexaflouride (SF6), and tritium (3H) sampled from the Pumphouse Lower Montane study site (wells PLM1, PLM6, and PLM7) within the East River Watershed, Colorado. The presented noble gas (PLM_noblegas_2021.csv) and environmental tracer (PLM_tracers_2021.csv) observation datasets, along with the associated modeling scripts, aide in quantifying groundwater residence times and recharge conditions in a high elevation mountain system. Furthermore, the modeling scripts quantify groundwater residence time and noble gas recharge condition uncertainties using a novel Markov-chain Monte Carlo approach. All data modeling scripts are written in the Python code.

54 ENVIRONMENTAL SCIENCES↗

STOCK: Structure mapper and online coarse-graining kit for molecular simulations

We present a web toolkit STructure mapper and Online Coarse-graining Kit for setting up coarse-grained molecular simulations. The kit consists of two tools: structure mapping and Boltzmann inversion tools. The aim of the first tool is to define a molecular mapping from high, e.g. all-atom, to low, i.e. coarse-grained, resolution. Using a graphical user interface it generates input files, which are compatible with standard coarse-graining packages, e.g. VOTCA and DL_CGMAP. Our second tool generates effective potentials for coarse-grained simulations preserving the structural properties, e.g. radial distribution functions, of the underlying higher resolution model. The required distribution functions can be provided by any simulation package. Simulations are performed on a local machine and only the distributions are uploaded to the server. The applicability of the toolkit is validated by mapping atomistic pentane and polyalanine molecules to a coarse-grained representation. Effective potentials are derived for systems of TIP3P (transferable intermolecular potential 3 point) water molecules and salt solution. The presented coarse-graining web toolkit is available at http://stock.cmm.ki.si.

74 ATOMIC AND MOLECULAR PHYSICS↗

An Exact Algorithm for the Linear Tape Scheduling Problem

Magnetic tapes are often considered as an outdated storage technology, yet they are still used to store huge amounts of data. Their main interests are a large capacity and a low price per gigabyte, which come at the cost of a much larger file access time than on disks. With tapes, finding the right ordering of multiple file accesses is thus key to performance. Moving the reading head back and forth along a kilometer long tape has a non-negligible cost and unnecessary movements thus have to be avoided. However, the optimization of tape request ordering has rarely been studied in the scheduling literature, much less than I/O scheduling on disks. For instance, minimizing the average service time for several read requests on a linear tape remains an open question. Therefore, in this paper, we aim at improving the quality of service experienced by users of tape storage systems, and not only the peak performance of such systems. To this end, we propose a reasonable polynomial-time exact algorithm while this problem and simpler variants have been conjectured NP-hard. We also refine the proposed model by considering U-turn penalty costs accounting for inherent mechanical accelerations. Then, we propose a low-cost variant of our optimal algorithm by restricting the solution space, yet still yielding an accurate suboptimal solution. Finally, we compare our algorithms to existing solutions from the literature on logs of the mass storage management system of a major datacenter. This allows us to assess the quality of previous solutions and the improvement achieved by our low-cost algorithm. Aiming for reproducibility, we make available the complete implementation of the algorithms used in our evaluation, alongside the dataset of tape requests that is, to the best of our knowledge, the first of its kind to be publicly released.

Honoré, Valentin↗

Speaker-targeted Synthetic Speech Detection

Text-to-speech technologies are evolving quickly towards realistic-sounding human-like voices. As this technology improves, so does the opportunity for malpractice in speaker identification (SID) via spoofing, the process of impersonating a voice biometric via synthesis. More data typically equates to a more realistic voice model, which poses an issue for well-known subjects, such as politicians and celebrities, who have vast amounts of multimedia available online. Detection of synthetic speech has relied on signal processing techniques that focus on the generation of new acoustic features and train deep learning models to detect when an audio file has been manipulated through the characterization of unnatural changes or artifacts. However, these techniques do not use any information from the speaker they are evaluating. This paper proposes to incorporate information from the speaker-of-interest (SoI) into the models to avoid specific spoofing attacks for certain vulnerable people. The wealth of data for well-known people can also be used to train a speaker-specific spoofing detector with a higher level of accuracy than a speaker-independent model. The paper proposes a new xResNet-PLDA system and compares it to three different baseline systems: a state-of-the-art speaker identification system, an xResNet system trained to discriminate between bona fide and fake speech, and a speaker identification system in which the PLDA and calibration models were trained with bona fide and fake speech. We evaluated the systems in two different scenarios — a cross-validation scenario and a hold-out scenario — with three different databases. We show how the proposed system outperforms dramatically the baseline systems in each scenario and for each database. Finally, we show how using a small amount of the SoI’s speech to adapt global calibration parameters improves the performance of the system, especially in unseen conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An Overview of the Database Framework for GEM Detector under CMS Experiment at CERN

In this paper, we give an overview of the database framework which we have developed for the Gas Electron Multiplier (GEM) Detector at CERN. The GEM constitutes a powerful addition to the family of fast radiation detectors; originally developed for particle physics experiments, and has spawned a large number of developments and applications. The GEM database framework comprises four components. The first component is the database itself. There are three instances of the database which have been deployed. One is for the development purpose which contains test data, other one is for the integration purposes while the last one is for the production purpose which contains real data. The database further comprises various schemas and each schema consists of different tables in it. We use separate schemas for various types of tables. The second component of the database framework is called DB Loader. The DB Loader is used to load data into database. The data is prepared in the predefined format which is in the XML form. Then the xml file is copied into a spool area of the server in which DB loader is running. Once the file is copied, the DB Loader loads the file into the database. The loader returns appropriate status codes after performing database insertion/update operation. The status of the database operations is checked against the status code which is returned by the loader. The third component of the database framework comprises graphical user interface (GUI). This is a web-based interface which can be accessed from the internet. This interface is basically used for the detector construction and to perform various quality control tests on the detector and its components. The last component of the database framework is called online monitoring system (OMS). The OMS is data visualization framework for the various detectors of the CMS experiment at CERN. It is also used to display data for the GEM. It enables users to view and retrieve database contents without having to learn database specifics.

Imran, Muhammad↗

High-density latch arrays

A system and device are provided for implementing memory arrays using high-density latch cells. The device includes an array of cells arranged into columns and rows. Each cell comprises a latch cell that includes a transmission gate, a pair of inverters, and an output buffer. Each row of latch cells is connected to at least one common node for addressing the row of latch cells, and each column of latch cells is connected to a particular bit of an input signal and a particular bit of an output signal. A register file may be implemented using one or more arrays of the high-density latch cells to replace any or all of the banks of SRAM cells typically used to implement the register file.

Sinangil, Mahmut Ersin↗