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At least 757 records · Page 42

Standardized Residue Numbering and Secondary Structure Nomenclature in the Class D β-Lactamases

Over 1370 class D β-lactamases are currently known, and they pose a serious threat to the effective treatment of many infectious diseases, particularly in some pathogenic bacteria where evolving carbapenemase activity has been reported. Detailed understanding of their molecular biology, enzymology, and structural biology are critically important, but the lack of a standardized residue numbering scheme and inconsistent secondary structure annotation has made comparative analyses sometimes difficult and cumbersome. Compounding this, in the post-AlphaFold world where we currently find ourselves, an extraordinary wealth of detailed structural information on these enzymes is literally at our fingertips; therefore it is vitally important that a standard numbering system is in place to facilitate the accurate and straightforward analysis of their structures. In conclusion, here we present a residue numbering and secondary structure scheme for the class D enzymes based on the sequence and structure of OXA-48 and apply it to test targets to demonstrate the ease with which it can be used.

59 BASIC BIOLOGICAL SCIENCES↗

Elucidating the Molecular Origins of the Transference Number in Battery Electrolytes Using Computer Simulations

The rate at which rechargeable batteries can be charged and discharged is governed by the selective transport of the working ions through the electrolyte. Conductivity, the parameter commonly used to characterize ion transport in electrolytes, reflects the mobility of both cations and anions. The transference number, a parameter introduced over a century ago, sheds light on the relative rates of cation and anion transport. This parameter is, not surprisingly, affected by cation–cation, anion–anion, and cation–anion correlations. In addition, it is affected by correlations between the ions and neutral solvent molecules. Computer simulations have the potential to provide insights into the nature of these correlations. We review the dominant theoretical approaches used to predict the transference number from simulations by using a model univalent lithium electrolyte. In electrolytes of low concentration, one can obtain a quantitative model by assuming that the solution is made up of discrete ion-containing clusters–neutral ion pairs, negatively and positively charged triplets, neutral quadruplets, and so on. These clusters can be identified in simulations using simple algorithms, provided their lifetimes are sufficiently long. In concentrated electrolytes, more clusters are short-lived and more rigorous approaches that account for all correlations are necessary to quantify transference. Elucidating the molecular origin of the transference number in this limit remains an unmet challenge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-speed tunable generation of random number distributions using actuated perpendicular magnetic tunnel junctions

Perpendicular magnetic tunnel junctions (pMTJs) actuated by nanosecond pulses are emerging as promising devices for true random number generation (TRNG) due to their intrinsic stochastic behavior and high throughput. In this work, we demonstrate the tunability and quality of random number distributions generated by pMTJs operating at a frequency of 104 MHz. First, changing the pulse amplitude is used to systematically vary the probability bias. The variance of the resulting bitstreams closely matches the expected binomial distribution, demonstrating consistency with an underlying sequence of Bernoulli trials. Second, the quality of uniform distributions of 8-bit random numbers generated with a probability bias of 0.5 is considered. A reduced chi-square analysis of these data shows that only two XOR operations are sufficient to achieve this distribution with p-values greater than 0.05. Finally, we show that there is a correlation between long-term probability bias variations and pMTJ resistance. These findings suggest that variations in the characteristics of the pMTJ underlie the observed variation of probability bias. In conclusion, our results highlight the potential of stochastically actuated pMTJs for high-speed, tunable TRNG applications, showing the importance of the stability of pMTJ device characteristics in achieving reliable, long-term performance.

Magnetic tunnel junctions↗

Ion Number Density Quantification Utilizing Pulsing Frequency in Negative Differential Resistance (NDR) Regime of Microplasma Operation

A mathematical model is presented for quantifying the ion number density over a range of discharge current in microplasma discharges. The ion number density is determined from measured discharge voltage, current, pulsing frequency, and trace impurity that is injected into the system deliberately. Experiments are conducted in pure helium with nitrogen being introduced as the trace species. The ion number density is estimated over a range of discharge current and is compared with multidimensional simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Retrieved Number concentration of Cloud Condensation Nuclei (RNCCN) Value-Added Product (VAP)

The objective of Retrieved Number concentration of Cloud Condensation Nuclei (RNCCN) Value-Added Product (VAP) is to provide the vertical distribution of cloud condensation nuclei (CCN) number concentrations to better represent aerosol indirect effects in climate models. The RNCCN VAP allows to collect a large number of independent samples of vertical CCN measurements at various supersaturation values from the ground. This helps to avoid the high cost of aircraft and increases the temporal distribution of retrieved CCN in the planetary boundary layer. The VAP method is based on Ghan and Collins (2004) and Ghan et al. (2006) proposed parameterizations that retrieve the vertical profiles of CCN directly from the ground level CCN, humidification factor, and in-situ lidar measurements. Further, the VAP accuracy is improved by using the quality controlled data that ensures that the boundary layer is well mixed.

54 ENVIRONMENTAL SCIENCES↗

Weber Number Tests in the NASA Icing Research Tunnel

A study of the Weber Number effects on droplets in the NASA Icing Research Tunnel is described. The work focuses on examining the droplet Weber Number effects observed for droplets accelerated by air flow in the contraction section of the Icing Research Tunnel to the test section. These results will aid in Supercooled Large Drop facility design studies. Measurements acquired with the Phase Doppler Interferometer and High Speed Imaging Dual Range Flight Probes at a series of locations through the contraction are presented alongside a 1D numerical model developed during this study to aid interpretation of the experimental results. An estimate of the maximum Weber Number observed in the Icing Research Tunnel for varying drop sizes up to 1000 m is presented and provided for incorporation into future design studies. Finally, experimental results coupled with a numerical model indicate that breakup of drops up to 1000 m is not occurring in the NASA Icing Research Tunnel up to 129 m/s.

Icing Wind Tunnel↗

Weber Number Tests in the NASA Icing Research Tunnel

A study of the Weber Number effects on droplets in the NASA Icing Research Tunnel is described. The work focuses on examining the droplet Weber Number effects observed for droplets accelerated by air flow in the contraction section of the Icing Research Tunnel to the test section. These results will aid in Supercooled Large Drop facility design studies. Measurements acquired with the Phase Doppler Interferometer and High Speed Imaging Dual Range Flight Probes at a series of locations through the contraction are presented alongside a 1D numerical model developed during this study to aid interpretation of the experimental results. An estimate of the maximum Weber Number observed in the Icing Research Tunnel for varying drop sizes up to 1000 μm is presented and provided for incorporation into future design studies. Finally, experimental results coupled with a numerical model indicate that breakup of drops up to 1000 μm is not occurring in the NASA Icing Research Tunnel up to 129 m/s.

Icing Wind Tunnel↗

Observations of Particle Number Size Distributions and New Particle Formation in Six Indian Locations

Atmospheric new particle formation (NPF) is a crucial process driving aerosol number concentrations in the atmosphere; it can significantly impact the evolution of atmospheric aerosol and cloud processes. This study analyses at least 1 year of asynchronous particle number size distributions from six different locations in India. We also analyze the frequency of NPF and its contribution to cloud condensation nuclei (CCN) concentrations. We found that the NPF frequency has a considerable seasonal variability. At the measurement sites analyzed in this study, NPF frequently occurs in March–May (pre-monsoon, about 21 % of the days) and is the least common in October–November (post-monsoon, about 7 % of the days). Considering the NPF events in all locations, the particle formation rate (J_(SDS)) varied by more than 2 orders of magnitude (0.001–0.6 /cu.cm s) and the growth rate between the smallest detectable size and 25 nm (GR_(SDS-25 nm)) by about 3 orders of magnitude (0.2–17.2 nm/h). We found that JSDS was higher by nearly 1 order of magnitude during NPF events in urban areas than mountain sites. GRSDS did not show a systematic difference. Our results showed that NPF events could significantly modulate the shape of particle number size distributions and CCN concentrations in India. The contribution of a given NPF event to CCN concentrations was the highest in urban locations (4.3 × 10^(3) /cu.cm per event and 1.2 × 10^(3)/cu.cm per event for 50 and 100 nm, respectively) as compared to mountain background sites (2.7 × 10^(3)/cu.cm per event and 1.0 × 10^(3)/cu.cm per event, respectively). We emphasize that the physical and chemical pathways responsible for NPF and factors that control its contribution to CCN production require in situ field observations using recent advances in aerosol and its precursor gaseous measurement techniques.

particle number size distributions↗

Transforming an Ionic Conductor into an Electronic Conductor via Crystallization: In Situ Evolution of Transference Numbers and Structure in (La,Sr)(Ga,Fe)O 3–x Perovskite Thin Films

Mixed-conducting perovskites are workhorse electrochemically active materials, but typical high-temperature processing compromises their catalytic activity and chemo-mechanical integrity. Low-temperature pulsed laser deposition of amorphous films plus mild thermal annealing is an emerging route to form homogeneous mixed conductors with exceptional catalytic activity, but little is known about the evolution of the oxide-ion transport and transference numbers during crystallization. Here the coupled evolution of ionic and electronic transport behavior and structure in room-temperature-grown amorphous (La,Sr)(Ga,Fe)O 3-x films as they crystallize is explored. In situ ac-impedance spectroscopy with and without blocking electrodes, simultaneous capturing-synchrotron-grazing-incidence X-ray diffraction, dc polarization, transmission electron microscopy, and molecular dynamics simulations to evaluate isothermal and non-isothermal crystallization effects and the role of grain boundaries on transference numbers is combined. Ionic conductivity increases by ≈2 orders of magnitude during crystallization, with even larger increases in electronic conductivity. Consequently, as crystallinity increases, LSGF transitions from a predominantly ionic conductor to a predominantly electronic conductor. The roles of evolving lattice structural order, microstructure, and defect chemistry are examined. Grain boundaries appear relatively nonblocking electronically but significantly blocking ionically. The results demonstrate that ionic transference numbers can be tailored over a wide range by tuning crystallinity and microstructure without having to change the cation composition.

36 MATERIALS SCIENCE↗

Decomposition of Feynman integrals by multivariate intersection numbers

We present a detailed description of the recent idea for a direct decomposition of Feynman integrals onto a basis of master integrals by projections, as well as a direct derivation of the differential equations satisfied by the master integrals, employing multivariate intersection numbers. We discuss a recursive algorithm for the computation of multivariate intersection numbers, and provide three different approaches for a direct decomposition of Feynman integrals, which we dub the straight decomposition, the bottom-up decomposition, and the top-down decomposition. These algorithms exploit the unitarity structure of Feynman integrals by computing intersection numbers supported on cuts, in various orders, thus showing the synthesis of the intersection-theory concepts with unitarity-based methods and integrand decomposition. We perform explicit computations to exemplify all of these approaches applied to Feynman integrals, paving a way towards potential applications to generic multi-loop integrals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Stochastic Quasi-Newton Method in the Absence of Common Random Numbers

We present Q-SASS, a quasi-Newton method for unconstrained stochastic optimization that does not rely on common random numbers. Most existing quasi-Newton approaches leverage common random numbers to construct second-order updates. However, motivated by challenges in variational quantum algorithms—where such coordination is not possible—we consider the setting in which function values and gradients are accessible only through noisy probabilistic zeroth- and first-order oracles, and no common random numbers can be exploited. We derive high-probability tail bounds on the iteration complexity of our algorithm for nonconvex, convex, and strongly convex (more generally, those satisfying the PL condition) objective functions. Finally, we demonstrate the empirical benefits of our quasi-Newton updating scheme on both synthetic and quantum chemistry problems.

Complexity bound↗

Toward computing bounds for Ramsey numbers using quantum annealing

Quantum annealing is a powerful tool for solving and approximating combinatorial optimization problems, such as graph partitioning, community detection, centrality, routing problems, and more. In this paper we explore the use of quantum annealing as a tool for use in exploring combinatorial mathematics research problems. We consider the monochromatic triangle problem and the Ramsey number problem, both examples of graph coloring. Conversion to quadratic unconstrained binary optimization (QUBO) form is required to run on quantum hardware. While the monochromatic triangle problem is quadratic by nature, the Ramsey number problem requires the use of order reduction methods for a quadratic formulation. The goal is to provide a method for producing special colorings of graphs which if successful would provide lower bounds for certain Ramsey numbers. We discuss implementations, limitations, and results when running on the D-Wave Advantage quantum annealer.

97 MATHEMATICS AND COMPUTING↗

Distributed non-negative matrix factorization with determination of the number of latent features

The holistic analysis and understanding of the latent (that is, not directly observable) variables and patterns buried in large datasets is crucial for data-driven science, decision making and emergency response. Such exploratory analyses require devising unsupervised learning methods for data mining and extraction of the latent features, and non-negative matrix factorization (NMF) is one of the prominent such methods. NMF is based on compute-intense non-convex constrained minimization, which, for large datasets requires fast and distributed algorithms. However, current parallel implementations of NMF fail to estimate the number of latent features. In practice, identifying these features is both difficult and significant for pattern recognition and latent feature analysis, especially for large dense matrices. Here, we introduce a distributed NMF algorithm coupled with distributed custom clustering followed by a stability analysis on dense data, which we call DnMFk, to determine the number of latent variables. The results on synthetic data and the classical Swimmer data set demonstrate the accuracy of model determination while scaling nearly linearly across multiple processors for large data. Further, we employ DnMFk to determine the number of hidden features from a terabyte matrix.

97 MATHEMATICS AND COMPUTING↗

Natural transformation as a tool in Acinetobacter baylyi : Evolution by amplification of gene copy number

For many years, the natural competency of Acinetobacter baylyi ADP1 facilitated studies of bacterial metabolism, biochemistry, and physiology. With the advent of synthetic biology, new opportunities arise to exploit the remarkable transformability and chromosomal plasticity of this model organism. In this chapter, we describe a recently developed method, “Evolution by Amplification and Synthetic Biology” (EASy). EASy allows the targeted amplification of chromosomal segments that give rise to new phenotypes. Increased gene dosage regulates protein expression in a rudimentary fashion by establishing a chromosomal array in which copy number adjusts via recombination between repeated DNA sequences. Selective conditions enrich for cells within the population that confer a growth advantage. Under continuous selective pressure, beneficial mutations may accumulate in any genomic region. Such mutations favor decreases in the average copy number of the target region. Thus, the genetic flexibility afforded by transient copy number variation helps accelerate the selection of engineered strains with desired traits during laboratory evolution. As a result, thanks to the extremely simple genetic manipulation of Acinetobacter baylyi ADP1, the EASy method can be readily implemented by researchers without the need for advanced instrumentation or complex cloning techniques.

59 BASIC BIOLOGICAL SCIENCES↗

On a fully-implicit VMS-stabilized FE formulation for low Mach number compressible resistive MHD with application to MCF

This study presents the development and evaluation of a fully-implicit variational multiscale (VMS) stabilized unstructured finite element (FE) formulation for compressible magnetohydrodynamics (MHD) model, at low Mach number regime. The model describes the dynamics of a compressible conducting fluid in the low Mach number limit in the presence of electromagnetic fields and can be used to study aspects of astrophysical phenomena, important science and technology applications, and basic plasma physics phenomena. The specific applications that motivate this study are macroscopic simulations of the longer time-scale stability and disruptions of magnetic confinement fusion (MCF) devices, specifically the ITER tokamak. The discussion considers the development of the VMS FE representation, the structure of the stabilizing terms that deal with significant convective flows, the stabilization of the nearly incompressible response of the fluid flow, and the stabilization of the constraint that enforces the solenoidal involution on the magnetic field. The nonlinear discretized system is solved with scalable preconditioned Newton–Krylov iterative methods, which employs a multiphysics block preconditioning method based on approximate block factorizations and Schur complements. The study presents an evaluation of the VMS method on a 2D cartesian tearing mode instability, and illustrates the scalability of the solvers on MCF relevant problems. A set of results are also presented for longer time-scale stability and disruptions for the ITER tokamak. These include a vertical displacement event (VDE), and a (1,1) internal kink mode. Here, the formulation is demonstrated to be scalable and also reasonably robust with respect to the Lundquist number scaling.

42 ENGINEERING↗

Number of surface sites and turnover frequencies for oxide catalysts

Unlike for metal catalysts where selective chemisorption probes (H 2 , O 2 , CO and N 2 O) have been successfully applied to count the number of active surface sites and allow determination of TOF values, the analogous situation for oxide catalysts has developed very slowly. The reason for the sluggish development of selective chemisorption probes for oxides is that the same chemisorption probes that work well with metals aren’t compatible with oxides since these chemical probes weakly adsorb on oxides. Methanol, however, is a very reactive molecule that has been found to readily chemisorb on oxides and allows for quantitative determination of the number of active surface sites (Ns). Here, in this mini-review, the determination of the number of active sites by methanol chemisorption is reviewed with examples for pure oxides (one-component oxides), supported oxides (submonolayer, monolayer and above monolayer) and bulk mixed oxides (surface enriched oxide present in submonolayer, monolayer and in excess of monolayer coverages).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Estimating QSVT angles for matrix inversion with large condition numbers

Quantum Singular Value Transformation (QSVT) is a state-of-the-art, near-optimal quantum algorithm that can be used for matrix inversion. The QSVT circuit is parameterized by a sequence of angles that must be pre-calculated classically, with the number of angles increasing as the matrix condition number grows. Computing QSVT angles for ill-conditioned problems is a numerically challenging task. Here, we propose a numerical technique for estimating QSVT angles for large condition numbers. This technique allows one to avoid expensive numerical computations of QSVT angles and to emulate QSVT circuits for solving ill-conditioned problems.

97 MATHEMATICS AND COMPUTING↗

Thermodynamic stability of elemental boron allotropes with varying numbers of interstitial atoms

Elemental boron exists in multiple allotropes, each characterized by structures containing icosahedral subunits. These structures have interstitial sites between the icosahedral subunits that are partially occupied. The number of atoms in the unit cell varies depending on the occupancy of these interstitial sites. Here we have investigated the thermodynamic stability of boron allotropes for different numbers of atoms in the unit cell by calculating the free energies, including the contribution of phonons. It has been found that β-rhombohedral boron is most stable with 107 atoms/cell at low temperatures, while it becomes most stable with 105 atoms/cell above 1700 K. This suggests the occurrence of a phase transition at this temperature, which could account for the large variation in the number of atoms in the unit cell for β-rhombohedral boron samples. α-tetragonal boron is consistently most stable with 52 atom/cell and becomes unstable with more than 52 atoms/cell. Similar to β-rhombohedral boron, β-tetragonal boron may undergo a phase transition between 192 and 190 atoms/cell configurations. However, the thermodynamic stability of pure β-tetragonal boron has been questioned in comparison with other allotropes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗