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Class B Materials Code Case to include: FY25 - High temperature design methodology, overview of ASME Section III (Division 5), Design for elevated temperature service, Goal to address current gaps, evaluation of proposed rules, allowable stress development, Class A materials (existing ASME approach), variable confidence index, data extrapolation, bounding value for SEE, and next steps.
Biofuel production from lignocellulosic biomass offers a transformative solution to reduce global fossil fuel dependency. Certain thermophilic anaerobes, including Clostridium thermocellum, show promise for renewable ethanol production due to their ability to break down plant material at high temperatures. However, achieving commercially viable ethanol yields has proven challenging despite extensive engineering efforts. Here, we characterized 27 ferredoxin:NADP + oxidoreductase (Fnor) enzymes for their enzyme activity, nicotinamide cofactor specificity, thermotolerance, and functional expression in C. thermocellum . We identified a subset of 10 of these enzymes as a novel class of Fnor enzymes suited for metabolic pathways aimed at high-titer ethanol production. When expressed in engineered C. thermocellum , these enzymes increased ethanol production up to 2.2-fold. These findings establish a novel ethanol pathway and provide insights into physiological roles and biotechnological applications of this new class of Fnor enzymes.
ABSTRACT Antimicrobial resistance inAcinetobacter baumanniiis partly mediated by chromosomal class C β-lactamases, theAcinetobacter-derived cephalosporinases (ADCs). Recently, a growing number of emerging variants were described, expanding this threat. Consistent with other β-lactamases, one of the main areas of variance exists in the Ω-loop region near the site of cephalosporin binding. Interestingly, a common alanine duplication (Adup) is found in this region. Herein, we studied specific Adup variants expressed in a uniformEscherichia coligenetic background that demonstrated high-level resistance to multiple oxyimino-cephalosporins. For ceftolozane and ceftazidime, the Adup ADCs significantly increased levels of resistance (minimum inhibitory concentration [MIC] ≥ 512 µg/mL and MIC ≥ 1,024 µg/mL, respectively). These observations were consistent with the increasedk cat /K M for ceftazidime. For cefiderocol, three Adup variants exhibited increased MICs and increasedk cat /K M for this compound. Timed electrospray ionization mass spectrometry demonstrated stable cephalosporin:ADC adducts with ADC-30 (non-Adup), but not with ADC-33 (Adup), consistent with turnover. The X-ray crystal structure of Adup variant ADC-33 in complex with ceftazidime was determined (1.57 Å resolution) and suggests that increased turnover is facilitated by conformational changes (shift in Tyr221 and orientation of the oxyimino portion of the R1 side chain) and repositioning of water in the active site. These changes appear to favor substrate-assisted catalysis as an alternative mechanism to base-assisted catalysis. These studies also provide unprecedented insight into the mechanism underlying oxyimino-cephalosporin hydrolysis by expanded-spectrum ADC β-lactamases and possibly other class C β-lactamases, which is of critical importance to future drug design. IMPORTANCE The characterization of emergingAcinetobacter-derived cephalosporinase (ADC) variants is necessary to understand the increasing resistance to β-lactam antibiotics inAcinetobacterspp. In this study, cefiderocol retains effectiveness against ADC variants with and without an Ω-loop alanine duplication (Adup). However, the presence of the Adup appears to introduce loop flexibility and structural alterations resulting in increased resistance and steady-state turnover of larger cephalosporins. Further characterization provides unprecedented insight into the mechanism of cephalosporin hydrolysis by ADC β-lactamases and supports a concomitant increase in ADC structural flexibility and cephalosporin affinity that leads to more efficient hydrolysis. In addition, the crystal structure of ADC-33 in complex with ceftazidime is consistent with a substrate-assisted catalysis mechanism. The structural differences in the ADC-33 active site leading to ceftazidime catalysis provide a better understanding of β-lactamase Adup variants and open important opportunities for future drug design and development.
ABSTRACT Influenza infection and vaccination impart strain-specific immunity that protects against neither seasonal antigenic variants nor the next pandemic. However, antibodies directed to conserved sites can confer broad protection. Here, we identify and characterize a class of human antibodies that engage a previously undescribed, conserved epitope on the influenza hemagglutinin (HA) protein. Prototype antibody S8V1-157 binds at the normally occluded interface between the HA head and stem. Antibodies to this HA head–stem interface epitope are non-neutralizingin vitrobut protect against lethal influenza infection in mice. These antibodies bind to most influenza A subtypes and seasonal human variants, and are present at low frequencies in the memory B cell populations of multiple human donors. Vaccines designed to elicit these antibodies might contribute to “universal” influenza immunity. IMPORTANCE Antibodies to the influenza virus hemagglutinin (HA) protein confer the strongest protection against infection. Human antibodies elicited by infection and/or vaccination fail to protect against antigenically novel animal, pandemic, or human seasonal viruses. Improved vaccines are needed. We identify a novel class of antibodies that bind most divergent HA subtypes and all seasonal human HA antigenic variants tested. These antibodies confer protection from lethal influenza challenge in animal models. The corresponding epitope on the HA head is occluded by its interaction with the stem and is inaccessible in the well-resolved prefusion state. The immunogenicity of this head–stem interface indicates that poorly understood conformations of HA presenting widely conserved surfaces are explored in biochemical, cell-based, andin vivoassays. Head–stem interface antibodies warrant further investigation as an avenue to improve influenza vaccines and therapeutics.
This study addresses the challenges inherent in building use type classification, particularly focusing on the issue of class imbalance in the training datasets for machine learning classifiers. We comprehensively analyze the efficacy of various class-balancing sampling techniques. Employing Monte Carlo simulations and Bayesian optimization, we evaluated the performance of multiple sampling methods, including Random Oversampling, Random Undersampling, SMOTE, Borderline-SMOTE, and ADASYN, across a dataset encompassing nine southeastern coastal states of the United States. Our findings reveal that simple random over- and undersampling techniques outperform more sophisticated methods. Additionally, we show inherent value in creating an imbalance in training data to effectively train a machine learning classifier for distinguishing between residential and nonresidential buildings. This study provides valuable guidance for future research on building use type classification research and lays essential groundwork for developing attribute-rich building stock datasets.
Federated learning (FL) at leadership-class HPC systems remains largely unexplored, despite growing interest in deploying federated workflows on modern HPC systems. This paper provides the first system-level empirical characterization of federated fine-tuning of pretrained foundation models on an exascale supercomputer under a multi-node deployment. Using up to 96 concurrent FL clients deployed across Frontier nodes, we study the impact of client scale, model size, data heterogeneity, partial participation, and differential privacy on runtime, communication overhead, and convergence stability. Our results show that pretrained transformer models remain robust to heterogeneity, client dropout, and privacy noise, while system efficiency degrades rapidly with scale as synchronizat and orchestration dominate runtime. We further demonstrate that system-aware execution strategies, including intra-node aggregation and early aggregation, significantly reduce wall-clock time without degrading model quality. These findings establish a practical performance baseline and inform the design of communication-efficient FL systems on leadership-class HPC platforms.
Abstract Approved inhibitors of KRASG12C prevent oncogenic activation by sequestering the inactive, GDP-bound (OFF) form rather than directly binding and inhibiting the active, GTP-bound (ON) form. This approach provides no direct target coverage of the active protein. Expectedly, adaptive resistance to KRASG12C (OFF)-only inhibitors is observed in association with increased expression and activity of KRASG12C(ON). To provide optimal KRASG12C target coverage, we have developed BBO-8520, a first-in-class, direct dual inhibitor of KRASG12C(ON) and (OFF) forms. BBO-8520 binds in the Switch-II/Helix3 pocket, covalently modifies the target cysteine, and disables effector binding to KRASG12C(ON). BBO-8520 exhibits potent signaling inhibition in growth factor–activated states, in which current (OFF)-only inhibitors demonstrate little measurable activity. In vivo, BBO-8520 demonstrates rapid target engagement and inhibition of signaling, resulting in durable tumor regression in multiple models, including those resistant to KRASG12C(OFF)-only inhibitors. BBO-8520 is in phase 1 clinical trials in patients with KRASG12C non–small cell lung cancer. Significance: BBO-8520 is a first-in-class direct, small molecule covalent dual inhibitor that engages KRASG12C in the active (ON) and inactive (OFF) conformations. BBO-8520 represents a novel mechanism of action that allows for optimal target coverage and delays the emergence of adaptive resistance seen with (OFF)-only inhibitors in the clinic. See related commentary by Zhou and Westover, p. 455
This study investigates the recovery of building-level footfall from the COVID-19 pandemic using privacy-preserving mobile devices-based footfall data within 60 downtown areas in the USA and Canada. Using clustering, we identify five distinct building typologies based on their characteristics, including rent, quality and recovery rates. The results reveal significant variation of recovery rates by building features. We find negative relationships with footfall recovery for both the percentage of office and remote work tenants and building quality. In contrast, buildings with traditional work tenants and retail functions achieve higher recovery rates. We also test the ‘flight to quality’ hypothesis via on our typology results. High-quality office buildings (Class A+) continue to have high rents but experience low physical footfall recovery, which suggests that this class is not as resilient as portrayed. The findings thus suggest the importance of considering both economic and footfall resilience in evaluating the performance of office buildings.
We discuss a class of selection rules which i) do not come from group actions on fields, ii) are exact at tree level in perturbation theory, iii) are increasingly violated as the loop order is raised, and iv) eventually reduce to selection rules associated with an ordinary group symmetry. We start from basic field-theoretical examples in which fields are labeled by conjugacy classes rather than representations of a group, and discuss generalizations using fusion algebras or hypergroups. We also discuss how such selection rules arise naturally in string theory, such as for non-Abelian orbifolds or other cases with non-invertible worldsheet symmetries.
The Z line VISAR system (ZLV) is a spatially-resolved velocimeter that measures surface velocities in high-energy density experiments on the Z Pulsed Power Facility to facilitate the investigation of fusion, power flow, and dynamic material physics. The data measured in these experiments are analyzed with the LineVISAR SMASH class, a MATLAB software suite that provides tools for data importation, streak image correction, spatiotemporal registration, wrapped phase computation, phase unwrapping, shock handling, and velocity calculation. This report overviews the LineVISAR class, discusses its use, provides example implementations, and supplies analysis specifics not typically recorded in journal publications.
The Illinois Storage Corridor (ISC) project evaluated two distinct sites to determine the feasibility of commercial-scale CO₂ storage at each. The project leveraged the region's exceptional geological characteristics, particularly the well-characterized Cambro-Ordovician Storage Complex, to enable permanent geological storage of more than 50 million tonnes of CO₂ over 30 years. The two storage sites are located at One Earth Energy (OEE) facility in northcentral Illinois and Prairie State Generating Company (PSGC) in southcentral Illinois. Once operational, these facilities will combine to capture and store more than 6.5 million tonnes of CO₂ per year, positioning the ISC among the largest carbon storage regions globally. Preliminary homogeneous dynamic modeling based on regional and site-specific reservoir characteristics indicates promising injection capabilities at both locations. For the OEE site, modeling predicts a maximum allowable injection rate of 3.7 MTPA, with a baseline scenario of 1.7 MTPA over 30 years producing a CO₂ plume radius of 1.4 miles at end of injection. For the PSGC site, incorporating recent well data, modeling indicates a single-well maximum injection rate of 2.1 MTPA, with a plume radius of 4.2 miles at end of injection for the 60 MT over 30 years scenario. The primary objective of this CarbonSAFE Phase III project is to develop and submit Class VI Underground Injection Control (UIC) permit applications to the U.S. Environmental Protection Agency Region 5. The permitting plan outlines comprehensive site characterization, Area of Review delineation, monitoring programs, well construction designs, financial responsibility provisions, and post-injection site care procedures necessary to demonstrate safe, permanent CO₂ storage protective of underground sources of drinking water. Three UIC Class VI permit applications for the OEE site were submitted to EPA in October 2022 and are progressing through technical review, with final permit decision projected by June 2026. Through five rounds of Requests for Additional Information and responses, the applications have been refined to address computational modeling, area of review delineation, well integrity, monitoring protocols, and financial assurance requirements. For the PSGC site, finalized characterization and permitting documentation was delivered directly to the facility in July 2023 due to business constraints precluding formal federal regulatory submission. This comprehensive permitting effort builds upon extensive prior subsurface evaluations and demonstration projects that have confirmed the feasibility of widespread commercial-scale carbon storage in the region.
Class D β-lactamases (DBLs) represent a major threat to antibiotic efficacy by hydrolyzing β-lactam drugs, including last-resort carbapenems, thereby driving antimicrobial resistance in Gram-negative bacteria. The enzymes share a structurally conserved two-domain α/β architecture with seven active-site motifs and three flexible extended loops (the P-loop, Ω-loop, and newly designated B-loop) that surround the active site. While each of these loops is known to influence enzyme function, their coordinated roles have not been fully elucidated. To investigate the significance of their interplay, we compared the sequences and crystal structures of 40 DBLs from clinically relevant Gram-negative pathogens and performed molecular dynamics simulations on selected representatives. Combined structural and dynamical analyses revealed a strong correlation between B-loop architecture and carbapenemase activity in the pathogens Klebsiella and Acinetobacter, particularly regarding loop length and spatial organization. These findings emphasize the B-loop’s critical contribution, in concert with the P- and Ω-loops, in tuning active site versatility, substrate recognition, catalytic activity, and structural stability. A deeper understanding of how these motifs and loops govern DBL function may inform the development of novel antibiotics and inhibitors targeting this class of enzymes.
The Cosmology Large Angular Scale Surveyor (CLASS) is a telescope array that observes the cosmic microwave background (CMB) over ∼75% of the sky from the Atacama Desert, Chile, at frequency bands centered near 40, 90, 150, and 220 GHz. CLASS measures the large angular scale CMB polarization to constrain the tensor-to-scalar ratio and the optical depth to last scattering. This paper presents the optical characterization of the 90 GHz telescope. Observations of the Moon establish the pointing while dedicated observations of Jupiter are used for beam calibration. The standard deviations of the pointing error in azimuth, elevation, and boresight angle are 1$^{'}_.$3, 2$^{'}_.$1, and 2$^{'}_.$0, respectively, over the first 3 yr of observations. This corresponds to a pointing uncertainty ∼7% of the beam’s full width at half-maximum (FWHM). The effective azimuthally symmetrized instrument 1D beam estimated at 90 GHz has an FWHM of 0$^°_.$620 ± 0$^°_.$003 and a solid angle of 138.7 ± 0.6(stats.) ± 1.1(sys.) μsr integrated to a radius of 4°. The corresponding beam window function drops to $b^2_ℓ$ = 0.93, 0.71, 0.14 at ℓ = 30, 100, 300, respectively. Far-sidelobes are studied using detector-centered intensity maps of the Moon and measured to be at a level of 10 −3 or below relative to the peak. The polarization angle of Tau A estimated from preliminary survey maps is 149°.6 ± 0°.2(stats.) in equatorial coordinates. The instrumental temperature-to-polarization (T → P) leakage fraction, inferred from per-detector demodulated Jupiter scan data, has a monopole component at the level of 1.7 × 10 −3 , a dipole component with an amplitude of 4.3 × 10 −3 , with no evidence of quadrupolar leakage.
This dataset includes eight 1 × 1 km maps of the abundances of eight enzyme functional classes (EFC) for soil C, N, and P cycling across the CONUS. These mappings are predicted by the machine learning model trained using metagenomics and the corresponding environmental data. This item corresponds to our article: Fan, C., Song, Y., Mishra, U., Gautam, S., & Mayes, M. A. (2025). Harnessing the Power of Machine Learning and Omics to Identify Environmental Regulation on Microbial Functional Composition for Soil C, N, and P Cycling. Journal of Geophysical Research: Biogeosciences, 130(10).
The electric vehicles (EVs) market keeps growing globally; thus, it is critical to secure the EV charging communication protocols in order to guarantee reliable and fair charging operations among the customers. The Open Charge Point Protocol (OCPP) 2.0.1 supports the communication between the Electric Vehicle Supply Equipment (EVSE) and Charging Station Management Systems (CSMSs); therefore, it becomes vulnerable to several types of attacks, which aim to jeopardize smart charging, billing, and energy management. Specifically, OCPP 2.0.1 allows the self-reporting of the State of Charge (SOC) values, which makes it vulnerable to spoofing-based cyberattacks, which target manipulating the scheduling priorities, distorting the load forecasts, and extending the charging sessions in an unfair manner. In this paper, we try to address this type of attack by providing a comprehensive analysis of the SOC spoofing attacks and introducing a novel unsupervised detection framework based on the One-Class Support Vector Machine (OCSVM) algorithm. Specifically, two types of attack scenarios are analyzed (i.e., priority manipulation and session extension) by deriving engineered features that capture the nonlinear relationships under normal charging behavior. Detailed simulation-based results are derived by utilizing the DESL-EPFL Level 3 EV charging dataset. Our results demonstrate high F1-score and recall in identifying spoofed SOC values and that the proposed OCSVM model demonstrates superior performance compared to alternative clustering and deep-learning based detectors.
Sodium-ion batteries (SIBs) are entering commercial relevance as a sustainable and low-cost alternative to lithium-ion batteries. Improving the energy density of SIBs is critical to enable their widespread adoption. Here, in this work, a new class of cathode materials Na 6 M S 4 ( M = Co, Mn, Fe, and Zn) that exhibit high charge-storage capacity is reported. Using Na 6 CoS 4 as a prototypical example, a six-electron conversion reaction dominated by anion redox is observed, confirmed through various electrochemical and spectroscopic techniques. After the initial cycle, Na 6 CoS 4 delivers a high capacity of 392 mA h g -1 with a long lifespan of over 500 cycles. The reaction involves, initially, the transformation of crystalline Na 6 CoS 4 to a nearly amorphous structure consisting of mainly CoS and sulfur nanoparticles, which then reversibly cycles between nearly amorphous a-CoS/S and a-Na 6 CoS 4 . Such anion-redox-driven conversion-type cathodes hold the potential to enable energy-dense, stable SIBs.
Abstract Sodium‐based batteries are gaining momentum due to the abundance and lower cost of sodium compared to lithium. Solid‐state sodium batteries can also provide further safety advantages. However, sodium‐based solid‐state electrolytes (SSEs) that meet all the rigorous requirements, such as high ionic conductivity, oxidative stability with the cathode, and ease of processability, are lacking. We present here a new class of sodium‐based oxyhalide electrolytes NaNbCl 6‐2x O x with a facile mechanochemical synthesis. The oxyhalide NaNbCl 4 O exhibits close to two orders of magnitude higher ambient‐temperature sodium‐ion conductivity (1.03×10 −4 S cm −1 ) compared to the halide counterpart NaNbCl 6 (3×10 −6 S cm −1 ). Structural motifs unique to the oxygen content in NaNbCl 6‐2x O x are identified with 23 Na and 93 Nb magic angle spinning nuclear magnetic resonance (MAS NMR) spectroscopy and x‐ray diffraction (XRD). Solid‐state sodium batteries assembled with NaNbCl 4 O electrolyte and the cobalt‐ and nickel‐free layered Na 0.70 Fe 0.3 Mn 0.65 Al 0.05 O 2 cathode exhibit a maximum discharge capacity of 155 mAh g −1 with good cycle life at ambient temperature.
Abstract Sodium‐based batteries are gaining momentum due to the abundance and lower cost of sodium compared to lithium. Solid‐state sodium batteries can also provide further safety advantages. However, sodium‐based solid‐state electrolytes (SSEs) that meet all the rigorous requirements, such as high ionic conductivity, oxidative stability with the cathode, and ease of processability, are lacking. We present here a new class of sodium‐based oxyhalide electrolytes NaNbCl 6‐2x O x with a facile mechanochemical synthesis. The oxyhalide NaNbCl 4 O exhibits close to two orders of magnitude higher ambient‐temperature sodium‐ion conductivity (1.03×10 −4 S cm −1 ) compared to the halide counterpart NaNbCl 6 (3×10 −6 S cm −1 ). Structural motifs unique to the oxygen content in NaNbCl 6‐2x O x are identified with 23 Na and 93 Nb magic angle spinning nuclear magnetic resonance (MAS NMR) spectroscopy and x‐ray diffraction (XRD). Solid‐state sodium batteries assembled with NaNbCl 4 O electrolyte and the cobalt‐ and nickel‐free layered Na 0.70 Fe 0.3 Mn 0.65 Al 0.05 O 2 cathode exhibit a maximum discharge capacity of 155 mAh g −1 with good cycle life at ambient temperature.