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At least 91 records · Page 5

Exploring Black-box Adversarial Attacks on Low-rank Constrained Neural Networks

Low-rank compression has been shown as an effective tool to reduce parameter counts of convolutional and vision transformer architectures; however, low-rank training often reduces model robustness to adversarial perturbations. In this work, we explore the effects of low-rank training on black-box attacks, where attacked images are generated without knowledge of the low-rank parameters. We find that low-rank training is not sufficient as a black-box defense and can sometimes produce worse than expected as compared to baseline models. Influencing the spectrum of the low-rank models during training, which is known to increase model robustness against white-box attacks, improves black-box performance as well.

Schnake, Stefan [ORNL] (ORCID:0000000215183538)↗

Traceable Black-Box Watermarks For Federated Learning

Due to the distributed nature of Federated Learning (FL) systems, each local client has access to the global model, which poses a critical risk of model leakage. Existing works have explored injecting watermarks into local models to enable intellectual property protection. However, these methods either focus on non-traceable watermarks or traceable but white-box watermarks. We identify a gap in the literature regarding the formal definition of traceable black-box watermarking and the formulation of the problem of injecting such watermarks into FL systems. In this work, we first formalize the problem of injecting traceable black-box watermarks into FL. Based on the problem, we propose a novel server-side watermarking method, TraMark, which creates a traceable watermarked model for each client, enabling verification of model leakage in black-box settings. To achieve this, TraMark partitions the model parameter space into two distinct regions: the main task region and the watermarking region. Subsequently, a personalized global model is constructed for each client by aggregating only the main task region while preserving the watermarking region. Each model then learns a unique watermark exclusively within the watermarking region using a distinct watermark dataset before being sent back to the local client. Extensive results across various FL systems demonstrate that TraMark ensures the traceability of all watermarked models while preserving their main task performance.

Xu, Jiahao [University of Nevada, Reno]↗

Grey-box and ANN-based building models for multistep-ahead prediction of indoor temperature to implement model predictive control

Model-based predictive control (MPC) strategies for heating, ventilation, and air-conditioning (HVAC) systems present an opportunity to lower building energy consumption and operational costs. Such approaches rely on the development of a model to precisely forecast building thermal dynamics, such as room air temperature or heating/cooling rate, and make control-related decisions. The control-oriented modeling of building energy systems should be accurate in predicting indoor conditions and present low computational complexity. These features are the key challenge of implementing advanced control methods such as MPC. Extant studies on building modeling for MPC have focused on step-ahead forecasting techniques to forecast building thermal dynamics, while multistep-ahead forecasting is essential. Moreover, machine learning model suitable in case of the domain-based engineering expertise are also not available. To this aim, we perform a comparative analysis of the grey-box model based on a resistance-capacitance (RC) thermal network and a machine learning model composed of an artificial neural network (ANN) for multistep-ahead prediction of building thermal dynamics using current and historical data. Actual experimental data obtained from the Flexible Research Platform (FRP) in Oak Ridge National Laboratory (US) are used for estimation and validation purposes. The average root mean squared error (RMSE) of the grey-box and ANN models are 0.89 °C and 1.02°C, respectively. Finally, the results indicate that the grey-box model outperforms the ANN model in the considered validation periods in terms of accuracy and prediction stability.

42 ENGINEERING↗

Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration

Model predictive control (MPC) has been proven in simulations and pilot case studies to be a superior control strategy for large buildings. MPC can utilize the weather and occupancy schedule forecasts, together with the system model, to predict the future thermal behavior of the building and minimize the overall energy use and maximize thermal comfort. However, these advantages come with the cost of increased modeling effort, computational demands, communication infrastructure, and commissioning efforts. Thus a typical approach is to, often rapidly, simplify the building modeling and MPC optimization problem while paying a price of not reaching the full performance potential. It has been shown that by employing accurate physics-based models, MPC performance can be notably increased closer to its theoretical performance bound. However, implementation of such high-fidelity MPC in real buildings remains a challenge, resulting in a lack of successful field test studies. This work presents the methodology and field test demonstration of a computationally efficient implementation of the white-box MPC in an office building in Belgium. The detailed model of the building is based on first-principle physical equations. The deployment and supervision of MPC operation in a practical setting are supported by an automated cloud-based communication infrastructure. The motivating factor behind the cloud-based architecture is its compatibility with a commercially appealing control as a service concept. The building is equipped with a ground source heat pump (GSHP) and thermally activated building structures (TABS), where the combination of both is also known as GEOTABS. From a control perspective, GEOTABS buildings are particularly challenging systems due to large scale, complex heating, ventilation and air conditioning (HVAC) system, and slow dynamics with time delays. On the other hand, there is an increased potential for energy savings due to the high thermal mass, which acts as thermal storage. The MPC operation is demonstrated during the challenging transient seasons (switching between heating and cooling), and its performance is compared to a traditional rule-based controller (RBC). We provide a proof of concept of real MPC operation for the most difficult seasons with notable GSHP energy use savings equal to 53.5% and thermal comfort improvement by 36.9%. Other MPC applications found in the literature describe tests for only cooling or only heating, and up to now only for a black-box or a grey-box approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Shear Lag in a Plywood Sheet-stringer Combination Used for the Chord Member of a Box Beam

Theoretical and experimental investigations were made of the distribution of strains in a plywood sheet-stringer combination used as the chord member of a box beam acted upon by bending loads. The theoretical solution was obtained with the help of the principle of minimum potential energy and certain simplifying assumptions. Strain measurements were made on a build-up box beam by means of electrical-resistance strain gages connected with strain indicators. A very satisfactory agreement between the theoretical and experimental strains was obtained.

LOADS - BEAMS, BOX↗

Molecular cloning and characterization of a novel Y-box gene from planarian Dugesia japonica

Highlights: • A novel gene encoding a Y-box protein named DjY2 was cloned from Dugesia japonica. • DjY2 protein was structurally different from other Y-box proteins in planarians. • The expression patterns of DjY2 transcripts are different from DjY1 and DeY1. • DjY2 gene might participate in the regeneration process in planarian. Y-box binding protein (YB protein) is an ancient conserved multifunctional DNA/RNA-binding protein. A novel YB protein DjY2 gene from planarian Dugesia japonica was cloned by RACE method and characterized. This cDNA contains 689 bp with a putative open reading frame of 197 amino acids. It has a predicted molecular mass of 22.14 kDa and an isoelectric point of 9.67. Whole-mount in situ hybridization and relative quantitative real-time PCR were used to study the spatial and temporal expression pattern of DjY2 in the process of planarian regeneration. Results showed that DjY2 was expressed in many parts of the body in intact planarian, but the expression level was low in head and pharynx. The transcripts of DjY2 was significantly increased both at the head parts and the tail parts after amputation, especially at the site of cutting. The spatial expression gradually recovered to the state of intact planarian with the time of regeneration. Our results indicated that DjY2 might participate in the process of regeneration in planarian.

60 APPLIED LIFE SCIENCES↗

Successful post-translocation reproduction and genetic integration of eastern box turtles

Translocation is a conservation tool increasingly used in the recovery of at-risk species, including turtles, which are one of the world's most imperiled taxa. Post-release monitoring is essential to determine the outcomes of a given intervention and inform future efforts. However, monitoring typically focuses on post-release survival and spatial ecology whereas few studies assess the genetic and demographic outcomes. The eastern box turtle (Terrapene carolina carolina) is in decline throughout its range and is increasingly likely to be subject to translocations, including efforts to repatriate animals confiscated from the illegal wildlife trade. In 2019–2021, we translocated two groups of box turtles to the Savannah River Site in South Carolina, USA, including confiscated turtles (n = 208) and surrendered long-term captive turtles (LTC; n = 35). In 2022, we monitored a subset of confiscated (n = 12), LTC (n = 15), and sympatric resident (n = 8) females for reproductive output and genotyped their offspring and candidate sires to assign parentage. We found that all groups of females produced eggs at a similar rate and produced viable offspring but that the most recently translocated group (LTCs) displayed lower hatching success. Parentage assignment revealed that all groups sired offspring and mated with each other. Furthermore, our results broadly indicate that confiscated and LTC box turtles can successfully reproduce and genetically integrate following their release into wild populations, and that translocation may serve as a valuable tool for local population recovery.

59 BASIC BIOLOGICAL SCIENCES↗

Class-based separations of mixed solid–liquid systems with condensable solvent washing and extraction: The dilemma of pizza box recycling

As primary feedstocks deplete across the world, raw material extraction becomes increasingly expensive. Awareness of the environmental impact of primary extraction has motivated the development of energy- and reagent-efficient methods for material reuse. This work confronts an emblematic challenge of modern recycling: the soiled pizza box. While the fibers constituting corrugated cardboard are generally recyclable, pizza contaminants such as sauces and oils complicate their reuse, resulting in municipal prohibitions on the recycling of used pizza boxes in cardboard recycling streams and a representative of 275 kg/year per US household of food waste that is directed to landfill. This challenge is common to many materials, and engineering strategies must be developed to tackle complex/mixed feedstocks. To address the mixed composition of the pizza box (and similar materials), an environmentally benign, non-toxic organic solvent is applied to remove and fractionate components from mixed materials. The solvent employed in this process, dimethyl ether (DME), is a condensable hygroscopic gas, which facilitates its removal and recovery for reuse. Further, the results of this study indicate that 1) DME is capable of solubilizing and extracting components from soiled cardboard and other materials, (resulting in cardboard drier than new/unused cardboard) facilitating its recycling, and 2) the DME-soluble components of the system phase separate into aqueous and fatty acid/oil fractions (potentially ~27.5 kg/year per US household). Condensable solvent-driven washing and extraction enable the efficient separation of multiple intermediate product streams, suggesting a pathway to enable technology development necessary for achieving clean production in a circular economy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural and dynamic mechanisms for coupled folding and tRNA recognition of a translational T-box riboswitch

T-box riboswitches are unique riboregulators where gene regulation is mediated through interactions between two highly structured RNAs. Despite extensive structural insights, how RNA-RNA interactions drive the folding and structural transitions of T-box to achieve functional conformations remains unclear. Here, by combining SAXS, single-molecule FRET and computational modeling, we elaborate the folding energy landscape of a translational T-box aptamer consisting of stems I, II and IIA/B, which Mg 2+ -induced global folding and tRNA binding are cooperatively coupled. smFRET measurements reveal that high Mg 2+ stabilizes IIA/B and its stacking on II, which drives the pre-docking of I and II into a competent conformation, subsequent tRNA binding promotes docking of I and II to form a high-affinity tRNA binding groove, of which the essentiality of IIA/B and S-turn in II is substantiated with mutational analysis. We highlight a delicate balance among Mg 2+ , the intra- and intermolecular RNA-RNA interactions in modulating RNA folding and function.

59 BASIC BIOLOGICAL SCIENCES↗

Structural basis for tRNA decoding and aminoacylation sensing by T-box riboregulators

T-box riboregulators are a class of cis-regulatory RNAs that govern the bacterial response to amino acid starvation by binding, decoding and reading the aminoacylation status of specific transfer RNAs. In this work, we provide a high-resolution crystal structure of a full-length T-box from Mycobacterium tuberculosis that explains tRNA decoding and aminoacylation sensing by this riboregulator. Overall, the T-box consists of decoding and aminoacylation sensing modules bridged by a rigid pseudoknot structure formed by the mid-region domains. Stem-I and the Stem-II S-turn assemble a claw-like decoding module, while the antiterminator, Stem-III, and the adjacent linker form a tightly interwoven aminoacylation sensing module. The uncharged tRNA is selectively recognized by an unexpected set of favorable contacts from the linker region in the aminoacylation sensing module. A complex structure with a charged tRNA mimic shows that the extra moiety dislodges the linker, which is indicative of the possible chain of events that lead to alternative base-pairing and altered expression output.

59 BASIC BIOLOGICAL SCIENCES↗

Commissioning of a replacement subatmospheric cold box for Jefferson Lab’s Central Helium Liquefier

Jefferson Lab’s Cryogenics Department has designed, fabricated, installed, and commissioned a new subatmospheric cold box to replace one of the two existing units within our Central Helium Liquefier (CHL). The replacement cold box, dubbed SC1R, pumps saturated helium vapor at 0.0385 atm from Jefferson Lab’s continuous electron beam accelerator facility (CEBAF) cryomodules to maintain an operating temperature of nominally 2.1 K. This is accomplished using a five-stage cryogenic centrifugal compressor (cold compressor) system and a brazed aluminum plate-fin heat exchanger operating between 2.1 K and 4.5 K. In this paper we will describe our experience commissioning the SC1R cold box. We will discuss pump-down of the system to 2.1 K and steady-state operation at the cold compressor design flow rates of 170, 200, and 250 g/s. Performance of the heat exchanger and cold compressors has been mapped across a range of flow rates and optimized for CEBAF operations. This commissioning data will be used to monitor future performance and adapt to changing load requirements.

Mastracci, B.↗

Conceptual design of a replacement 2.1 K cold box for the Spallation Neutron Source Central Helium Liquefier

Abstract After more than 20 years of operation, the cold compressor technology in use at the Spallation Neutron Source (SNS) is obsolete, and replacement parts and service are no longer available. SNS has partnered with Jefferson Lab to design and construct a replacement sub-atmospheric cold box outfitted with modern cold compressor technology. The general design follows from Jefferson Lab’s experience on other recent sub-atmospheric cold box projects. Design decisions are backed by thorough engineering analysis to ensure technical requirements are met in a cost-effective manner. Conceptual design of the replacement cold box has been completed, and will be summarized in this paper. It features five cold compressors with an operating flow range of 80-140 g/s, and includes piping and valving to support cold compressor maintenance without interrupting flow circulation to the load. The approach to thermal shielding, insulation, and integration of the upgraded cold compressor hardware into the existing SNS control system will also be addressed.

Mastracci, B [Thomas Jefferson National Accelerato↗

Commissioning plan for LCLS II 2 K cold box

Commissioning of the LCLS II cryogenic plant has been planned with respect to electrical and mechanical systems checkout, equipment cleanup, cool-down, and individual performance evaluation. This plant consists of warm and cold storage, helium compressors, 4.5 K and 2 K cold boxes, and all auxiliaries typical for helium refrigeration processes. The 2 K cold box, consisting of five cold compressors in series to produce the flow and pressures necessary for 2K operation, will be the last equipment installed and, along with an additional 10,000 L helium dewar, will allow the entire plant to be commissioned as a single entity. The pre-commissioning stages, commissioning plan for 2 K cold box without connecting to the LCLS II LINAC, additional test equipment needed to simulate the loads, all process studies and associated results are described herein.

36 MATERIALS SCIENCE↗

First-Principles Calculation of Electroweak Box Diagrams from Lattice QCD

We present the first realistic lattice QCD calculation of the $γ W$-box diagrams relevant for beta decays. The nonperturbative low-momentum integral of the $γ W$ loop is calculated using a lattice QCD simulation, complemented by the perturbative QCD result at high momenta. Using the pion semileptonic decay as an example, we demonstrate the feasibility of the method. By using domain wall fermions at the physical pion mass with multiple lattice spacings and volumes, we obtain the axial γ W -box correction to the semileptonic pion decay, $\square$$\frac{VA}{γW}|_π$ = 2.830 (11) stat (26 )syst × 10 –3 , with the total uncertainty controlled at the level of ~1% . This study sheds light on the first-principles computation of the $γ W$-box correction to the neutron decay, which plays a decisive role in the determination of $|V_ud|$ .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints (SHEBO) v1.0

SHEBO (surrogate optimization of problems with hidden constraints and expensive black-box objectives) is an efficient optimization algorithm that employs surrogate models to solve computationally expensive black-box simulation optimization problems that have hidden constraints. Hidden constraints are encountered when the objective function evaluation does not return a value for a parameter vector. These constraints are often encountered in optimization problems in which the objective function is computed by a black-box simulation code. SHEBO uses a combination of local and global search strategies together with an evaluability prediction function and a dynamically adjusted evaluability threshold to iteratively select new sample points.

Mueller, Juliane↗

Impacts of stochastic coalescence variability on warm rain initiation using Lagrangian microphysics in box and large-eddy simulations

Various coalescence methods for Lagrangian microphysics schemes are tested in box and large-eddy simulation (LES) models, including the stochastic all-or-nothing super-droplet method (SDM) and a version of SDM (dSDM) that applies a fractional approach similar to the average impact method. In LES, variabilities driven by microphysics and by flow realizations are separated using the “piggybacking” technique. Rain initiation averaged over many realizations of the box model is delayed and rain variability increases as the number of super-drops per collision volume ( N SD ) is decreased using SDM. In contrast, rain initiation time using SDM in LES is insensitive to N SD for 32 ≤ N SD ≤ 512. This is explained through the interaction between LES grid boxes, each acting as a separate collision volume. Variability across the ensemble of LES collision volumes using SDM results in rain quickly initiating in some of the LES grid cells at low N SD and leading to a similar overall timing of rain initiation from the cloud compared to simulations with high N SD . There is a ~20% decrease in the total rain mass and mean rain flux as N SD is increased from 32 to 256, with little additional change as N SD is increased from 256 to 512. The fractional coalescence approach in dSDM leads to reduced microphysical variability and a 15-18 min delay in rain initiation compared to SDM. Finally, an additional LES ensemble with microphysical variability feeding back to the dynamics shows that flow variability dominates the impact of microphysical variability on rain properties. Thus, flow variability must be constrained to isolate impacts of microphysical variability.

54 ENVIRONMENTAL SCIENCES↗

Report on High Energy Arcing Fault Experiments: Experimental Results from Open Box Enclosures

This report documents an experimental program designed to investigate High Energy Arcing Fault (HEAF) phenomena. The experiments focus on providing data to better characterize the arc to improve the prediction of arc energy emitted during a HEAF event. An open box experiment allow for direct observation of the arc, which allows diagnostic instrumentation to record the phenomenological data needed for better characterization of the arc energy source term. The data collected supports characterization of the arc and arc jet, enclosure breach, material loss, and electrical properties. These results will be used to better characterizing the hazard for improvements in fire probabilistic risk assessment (PRA) realism. The experiments were performed at KEMA Labs located in Chalfont, Pennsylvania. The experimental design, setup, and execution were completed by staff from the NRC, the National Institute of Standards and Technology (NIST), Sandia National Laboratories (SNL) and KEMA Labs. In addition, representatives from the Electric Power Research Institute (EPRI) observed some of the experimental setup and execution. The HEAF experiments were performed between August 22, 2020 and September 18, 2020 on near-identical 51 cm (20 in) cube metal boxes suspended from a Unistrut support structure. The three-phase arcing fault was initiated at the ends of the conductors oriented vertically and located at the center of the box. Either aluminum or copper conductors were used for the conductors. The low-voltage experiments used 1 000 volts AC, while the medium-voltage experiments used 6 900 volts AC consistent with other recently completed experiments. Durations of the experiment ranged from 1 s to 5 s with fault currents ranging from 1 kA to 30 kA. Real-time electrical operating conditions, including voltage, current and frequency, were measured during the experiments. Heat fluxes and incident energies were measured with plate thermometers, radiometers, and slug calorimeters at various locations around the electrical enclosures. The experiments were documented with normal and high-speed videography, infrared imaging and photography.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Heat transfer through a box beam from an impinging hydrogen flame

An analysis was performed to determine whether a hydrogen jet flame impinging on a tunnel ceiling composed of multiple prestressed steel reinforced concrete box beams could result in permanent damage to the tunnel. The lower layer of the concrete box beam was modeled to determine whether heat reaches the steel reinforcing bars and whether spalling could occur. Heat transfer analysis shows that the temperature remains constant at the location of the steel reinforcing bars after 1.3 minutes of impingement and reaches a maximum of 130°C after 5 minutes. However, assuming a constant impingement for 5 minutes is an over estimation due the existing fire model which includes conservative assumptions. Explosive spalling may occur at a thin layer (~0.05 in. at 50 seconds, 0.1 in. at 5 minutes) at the bottom surface of the concrete box beam, but the steel reinforcing bars will not be exposed to the hydrogen flame.

42 ENGINEERING↗