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At least 19 records

Correlation functions from tensor network influence functionals: The case of the spin-boson model

We investigate the application of matrix product state (MPS) representations of the influence functionals (IFs) for the calculation of real-time equilibrium correlation functions in open quantum systems. Focusing specifically on the unbiased spin-boson model, we explore the use of IF-MPSs for complex time propagation, as well as IF-MPSs for constructing correlation functions in the steady state. We examine three different IF approaches: one based on the Kadanoff–Baym contour targeting correlation functions at all times, one based on a complex contour targeting the correlation function at a single time, and a steady state formulation, which avoids imaginary or complex times, while providing access to correlation functions at all times. We show that within the IF language, the steady state formulation provides a powerful approach to evaluate equilibrium correlation functions.

Chemistry↗

Influence functions for the Delaware Oil and Gas Basin Tower Network

This data consists of influence functions created for the Delaware tower network for the purpose of calculating methane enhancements in the region. Two different footprint models were used. The Lagrangian Particle Dispersion model (LPDM, Uliasz 1993) was run from March 2020-May 2023. The model uses in-house WRF simulations for the meteorological transport as described in Barkley et al., (2023). Nine hundred (900) particles were released during each hourly period and are traced back 72 hours backwards in time. A static binning height of 110 m AGL was used to calculate surface influence. After May 2023, the LPDM simulations were phased out and replaced with influence functions created using HYSPLIT under the STILT configuration (Lin et al., 2003). The STILT influence functions use HRRR for the meteorological transport (Dowell et al., 2022). Nine hundred (900) particles were released during each hourly period and are traced back 72 hours backwards in time. A binning height of half the boundary layer height was used to calculate surface influence. Footprints are currently available from Sept 2020-December 2024 and will be updated periodically as more are generated in time. No STILT influence functions were created for tower site Maljimar, which was decommissioned in March 2022. Lat/Lon grid information for the LPDM influence functions is contained in lpdm-lat-lon-grid.nc. STILT grid information is contained within the influence functions themselves. Tower coordinates and heights can be found in tower-info.csv

Barkley, Z. R.↗

Real-time evolution of Anderson impurity models via tensor network influence functionals

In this work, we present and analyze two tensor network-based influence functional approaches for simulating the real-time dynamics of quantum impurity models such as the Anderson model. Via comparison with recent numerically exact simulations, we show that such methods accurately capture the long-time nonequilibrium quench dynamics. The two parameters that must be controlled in these tensor network influence functional approaches are a time discretization (Trotter) error and a bond dimension (tensor network truncation) error. We show that the actual numerical uncertainties are controlled by an intricate interplay of these two approximations, which we demonstrate in different regimes. Our work opens the door to using these tensor network influence functional methods as general impurity solvers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Understanding the tool influence function during sub-aperture belt-on-wheel glass polishing

The tool influence function (TIF) during sub-aperture belt-on-wheel polishing has been evaluated as a function of various process conditions (belt use/wear, dwell time, displacement, belt velocity, and wheel modulus and diameter) on fused silica glass workpieces using C e O 2 polishing media. TIF spots are circular or elliptical in shape with a largely flat bottom character. Furthermore, the volumetric removal rate varies significantly with belt use (or wear), stabilizing after ~<!-- ~ --> 15 m i n of use. A modified Preston model, where the pressure dependence is adjusted using a different scaling of the wheel modulus ( E w 0.5 ), largely predicts the volumetric removal rate over the range of process conditions evaluated. The relatively high volumetric removal rate of 30 -<!-- - --> 60 m m 3 / h using a fixed C e O 2 -in-resin-host belt offers a rapid, and hence, more economical, initial polish of aspheric and freeform optics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

How thermal fluctuations influence the function of the FeMo cofactor in nitrogenase enzymes

The catalytic mechanism of N 2 fixation by nitrogenase remains unresolved in how the strong N≡N bond is activated and why the reductive elimination of H 2 is required. Here, we use density functional theory and physiologically relevant thermal simulations to elucidate the mechanism of the complete nitrogenase catalytic cycle. Over the accumulation of four reducing equivalents, we find that protons and electrons transfer to the FeMo cofactor to weaken and break its bridge Fe–S bond, leading to temporary H 2 S formation that exposes the Fe sites to weakly bind N 2 . Remarkably, we find that subsequent H 2 formation is responsible for chemical activation to an N=N double bond accompanied by a low barrier for H 2 release. We emphasize that finite temperature effects smooth out mechanistic differences between DFT functionals observed at 0 K, thus leading to a consistent understanding as to why H formation is an obligatory step in N 2 adsorption and activation.

DFT↗

Influence of functional additives, fillers, and pigments on thermal and catalytic pyrolysis of polyethylene for waste plastic upcycling

Pyrolysis offers a relatively green and economical method to convert waste plastics into valuable chemicals and fuels without the need for harmful solvents, toxic chemicals, or costly high-pressure reactors. Despite its popularity among chemical upcycling technologies, industrial adoption suffers from feedstock heterogeneity, low-quality products, and catalyst deactivation. Most plastics in our daily lives are formulated with functional additives, fillers, and colorants. These additives remaining in end-of-life waste streams increase feedstock heterogeneity, creating a challenging issue in recycling plastics. Still, the potential impacts of additives on the chemical upcycling of plastics have been poorly understood. In this study, polyethylene compounded with a range of widely used additives (antioxidants, stabilizers, pigments, fillers, slip agents, and flame retardants) was subjected to both thermal pyrolysis and catalytic pyrolysis in different catalyst-to-feedstock contact modes. It showed that many inorganic additives, such as talc, kaolin, CaCO 3 , TiO 2 , carbon black, and zinc stearate, facilitated polymer decomposition during pyrolysis, increasing light hydrocarbons while also promoting aromatic and carbon residue formation. Conversely, antioxidants and stabilizers inhibited depolymerization, favoring heavier hydrocarbons. During catalytic pyrolysis with HZSM-5 zeolite, additives strongly enhanced aromatic and catalytic coke formation, especially when there was direct contact between plastics and catalysts. Although certain additives seem beneficial in the short term by promoting polymer cracking and improving the selectivity of aromatics, the transport of the additives and their degradation products and increased carbon coking can contaminate products, deactivate or modify catalysts, and foul reactors. These findings address a critical knowledge gap in effectively converting waste plastics via a greener route.

42 ENGINEERING↗

The effective number of parameters in kernel density estimation

We devise a new formula for measuring the effective degrees of freedom (EDoF) in kernel density estimation (KDE). Starting from the orthogonal polynomial sequence (OPS) expansion for the ratio of the empirical to the oracle density, we show how convolution with the kernel leads to a new OPS with respect to which one may express the resulting KDE. The expansion coefficients of the two OPS systems can then be related via a kernel sensitivity matrix, which leads to a natural oracle definition of EDoF through the trace operator. Asymptotic properties of the (empirical) plug-in EDoF are worked out through influence functions, and connections with other empirical EDoFs are established. Minimization of Kullback-Leibler divergence is investigated as an alternative to integrated squared error based bandwidth selection rules, yielding a new normal scale rule. The methodology, which arises from a proper oracle formulation and is not restricted to convolution kernels, suggests the possibility of a new bandwidth selection rule based on an information criterion such as AIC.

bandwidth selection↗

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

09 BIOMASS FUELS↗

Molecular-Level Insights into the Influence of Ionic Liquids on the Structure and Dynamics of Neutral and Charged Polyimides

We use all-atom molecular dynamics simulations to investigate how increasing ionic functionalization influences polyimide (PI) behavior in ionic liquid (IL) solvation environments. Here, we examine three polymer systems with varying charge densities: a neutral polyimide [N−PI] containing imidazole rings and progressively introduce charge through quaternization to create singly [C−PI] + and doubly charged [C−2PI] 2+ variants across a wide range of IL concentration (0−90 wt %). Through comprehensive structural, mechanical, and electrostatic analyses, we reveal that polymer charge density plays a central role in shaping IL organization and interaction with the polymer matrix. At low IL content, charged systems exhibit strong electrostatic complexation, leading to chain compaction, localized ESP environments, and elevated dielectric constants. As IL concentration increases, the effect of the different polymer charge states becomes less significant. Notably, an intermediate composition regime at approximately 50 wt % IL is associated with changes in IL-rich domain connectivity and overall system behavior across all three PI systems.

36 MATERIALS SCIENCE↗

Linguistic variation in functional types of statutory law

When the meaning of an ambiguous word, phrase or grammatical structure in a statutory provision is disputed, courts are tasked with identifying the best meaning of the contested language. A common method of resolving linguistic ambiguities is to investigate the meaning of the contested word or structure in statutory provisions with similar subject matter. While the subject matter of a text has a demonstrated effect on language use, register variation research shows that the function of a text is also highly influential in predicting linguistic variation. Thus far, the function of a statutory provision (e.g., obligation to act, authorization to act) has not been considered in legal interpretative research. In the present study, I investigate the extent to which function influences the lexico-grammatical characteristics of statutory texts. 2,573 statutory provisions from the Arizona State Code are individually assigned to one of seven categories representing their function: Duties, Permissions, Impersonal Rules, Operational Definitions, Prohibitions, Procedural Guidelines, and Criminal Offenses. Key feature analysis is used to identify and describe patterns of lexico-grammatical variation between the seven functional types. Results reveal a great deal of lexico-grammatical variation associated with function in the register of statutory law. Furthermore, some functional types of statutory provisions are more linguistically distinct than others. In conclusion, these findings suggest that it may be beneficial to consider communicative function when investigating legal interpretative questions.

99 GENERAL AND MISCELLANEOUS↗

Computer-controlled finishing via dynamically constraint position-velocity-time scheduler

In a Computer Numerical Controlled (CNC) finishing process, the target material removal from an optical surface is guided by the convolution between the influence function of a machine tool and its dwell time at certain points over the surface. To reduce dynamics stressing and increase machining efficiency, the dwell time must be converted to varying velocities, which are the actual inputs to the machine tool controller. Conventionally, the conversion assumed constant acceleration and relied on linear motion interpolation, which caused discontinuities in velocities. This unsmooth motion affects the material removal distribution, and, thus, the accuracy of the finished surface shape. Many modern CNC machines support the smoother, cubic-polynomial interpolated Position-Velocity-Time (PVT) motion mode; however, the conventional scheduler may fail to provide suitable velocities for the PVT. Here in this study answers this challenge by proposing a novel PVT-based velocity scheduler that achieves smooth motion while considering CNC dynamic limits. Firstly, the principle of the PVT is explained, and the PVT-based velocity scheduler is formulated. Secondly, a quadratic programming is used to optimize the velocities by imposing the CNC dynamic constraints and the C 1 continuities (zeroth and first derivatives are continuous) simultaneously. Thirdly, the smoothness and accuracy of the scheduled velocities are studied on different kinds of tool paths via simulation. Finally, a sub-0.3 nm level surface finishing experiment using ion beam figuring is demonstrated to verify the feasibility of the proposed method. The PVT-based scheduler and simulator code is open-sourced.

36 MATERIALS SCIENCE↗

Hydration and Restructuring of Polar Polymer Interfaces: Implications in Antifouling and Responsive Materials

Manipulating polymer interfaces is crucial for understanding how structure influences function in applications spanning biofouling prevention to energy storage. Moreover, observing how polymers adapt their microscopic structure to changes in their local environment can reveal essential properties that govern their performance in such applications, providing key insights into how to design more effective interfaces. Here, in this study, a series of “grafting-from” polymer brushes with side chains varying in charge, are probed by sum frequency generation (SFG) and modeled using all-atom molecular dynamics (MD) simulations to elucidate how chemical makeup and charge mediate interfacial restructuring in dry versus hydrated states. Results show that charge, in progressing from nonpolar to cationic to zwitterionic, results in dramatic changes in interfacial structure and overall hydration. While net neutral systems, regardless of bulk phase polarity, show minimal interfacial water structuring, the cationic species exhibits strong bulk water signals from the surface potential. Meanwhile, the polymer brushes themselves restructure in water differently independent of charge, impacting the functional groups that are presented to the aqueous phase. Nonpolar and cationic species for instance undergo a change in alkyl group orientations to accommodate hydrating water molecules, whereas the zwitterionic polymer becomes completely disordered in water. Overall, the structure-based behavior trends presented herein have implications in antifouling applications and responsive material interfaces.

biointerface↗

GRB2 dimerization mediated by SH2 domain-swapping is critical for T cell signaling and cytokine production

GRB2 is an adaptor protein required for facilitating cytoplasmic signaling complexes from a wide array of binding partners. GRB2 has been reported to exist in either a monomeric or dimeric state in crystal and solution. GRB2 dimers are formed by the exchange of protein segments between domains, otherwise known as “domain-swapping”. Swapping has been described between SH2 and C-terminal SH3 domains in the full-length structure of GRB2 (SH2/C–SH3 domain-swapped dimer), as well as between α-helixes in isolated GRB2 SH2 domains (SH2/SH2 domain-swapped dimer). Interestingly, SH2/SH2 domain-swapping has not been observed within the full-length protein, nor have the functional influences of this novel oligomeric conformation been explored. We herein generated a model of full-length GRB2 dimer with an SH2/SH2 domain-swapped conformation supported by in-line SEC–MALS–SAXS analyses. This conformation is consistent with the previously reported truncated GRB2 SH2/SH2 domain-swapped dimer but different from the previously reported, full-length SH2/C-terminal SH3 (C–SH3) domain-swapped dimer. Our model is also validated by several novel full-length GRB2 mutants that favor either a monomeric or a dimeric state through mutations within the SH2 domain that abrogate or promote SH2/SH2 domain-swapping. GRB2 knockdown and re-expression of selected monomeric and dimeric mutants in a T cell lymphoma cell line led to notable defects in clustering of the adaptor protein LAT and IL-2 release in response to TCR stimulation. These results mirrored similarly-impaired IL-2 release in GRB2-deficient cells. These studies show that a novel dimeric GRB2 conformation with domain-swapping between SH2 domains and monomer/dimer transitions are critical for GRB2 to facilitate early signaling complexes in human T cells.

59 BASIC BIOLOGICAL SCIENCES↗

Smoothing tool design and performance during subaperture glass polishing

During subaperture tool grinding and polishing, overlaps of the tool influence function can result in undesirable mid-spatial frequency (MSF) errors in the form of surface ripples, which are often corrected using a smoothing polishing step. Here, in this study, flat multi-layer smoothing polishing tools are designed and tested to simultaneously (1) reduce or remove MSF errors, (2) minimize surface figure degradation, and (3) maximize the material removal rate. A time-dependent convergence model in which spatial material removal varies with a workpiece-tool height mismatch, combined with a finite element mechanical analysis to determine the interface contact pressure distribution, was developed to evaluate various smoothing tool designs as a function of tool material properties, thicknesses, pad textures, and displacements. An improvement in smoothing tool performance is achieved when the gap pressure constant, $\overline{h}$ (which describes the inverse rate at which the pressure drops with a workpiece-tool height mismatch), is minimized for smaller spatial scale length surface features (namely, MSF errors) and maximized for large spatial scale length features (i.e., surface figure). Five specific smoothing tool designs were experimentally evaluated. A two-layer smoothing tool using a thin, grooved IC1000 polyurethane pad (with a high elastic modulus, E pad =360 MPa ), thicker blue foam (with an intermediate modulus, E foam =5.3 MPa ) underlayer, and an optimized displacement (d t =1 mm ) provided the best overall performance (namely, high MSF error convergence, minimal surface figure degradation, and high material removal rate).

47 OTHER INSTRUMENTATION↗

Understanding the Inner-Workings of Language Models Through Representation Dissimilarity

We use model stitching to understand the internal representations of language models. Similar to vision models, we find that "more is better," and representations learned with more data and larger width can improve the performance of weaker models via stitching. We likewise find that certain architecture choices, using GeLU vs SoLU activation functions, influence the quality of learned representations. Finally, model stitching (as opposed to other model diagnostic methods, like mode connectivity) can localize the different generalization strategies of text classifiers under domain shift to certain hidden layers.

Brown, Davis R.↗

Island influences on plant functional traits and trait–trait associations across species‐ and community‐scales

The island rule predicts gigantism or dwarfism in body size of island species relative to their mainland counterparts. However, whether other functional traits shift and whether trait–trait associations on islands differ between species and community levels remains unclear. We measured 13 carbon- and water-related functional traits in 37 shared tree species across 35 eastern Chinese islands and 66 nearby mainland plots. We examined species-level trait value shifts and associations under the island rule and compared trait associations between species and communities. Most size-related, wood-anatomical, and hydraulic traits shifted on islands, with large values decreasing and small values increasing; yet, their associations remained stable, aligning with the global trait spectrum and trait–trait coevolution. This stability, despite trait value shifts, suggests evolutionary integration of functional strategies. By contrast, island community-scale trait associations diverged from shared species-level patterns and sometimes reversed, such as positive relationships between wood density and resource-acquisitive traits. Community-level trait associations were stronger on islands, likely reflecting constrained environmental filtering and migration limitation. These contrasting patterns suggest that dominant species can restructure trait associations at the community level, with implications for ecosystem functioning and carbon storage, thereby advancing understanding of plant trait strategies in island systems.

Archipelagos↗