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At least 145 records · Page 8

Phosphate binding protein as the biorecognition element in a biosensor for phosphate

This work explores the potential use of a member of the periplasmic family of binding proteins, the phosphate binding protein (PBP), as the biorecognition element in a sensing scheme for the detection of inorganic phosphate (Pi). The selectivity of this protein originates from its natural role which, in Escherichia coli, is to serve as the initial receptor for the highly specific translocation of Pi to the cytoplasm. The single polypeptide chain of PBP is folded into two similar domains connected by three short peptide linkages that serve as a hinge. The Pi binding site is located deep within the cleft between the two domains. In the presence of the ligand, the two globular domains engulf the former in a hinge-like manner. The resultant conformational change constitutes the basis of the sensor development. A mutant of PBP (MPBP), where an alanine was replaced by a cysteine residue, was prepared by site-directed mutagenesis using the polymerase chain reaction (PCR). The mutant was expressed, from plasmid pSD501, in the periplasmic space of E. coli and purified in a single chromatographic step on a perfusion anion-exchange column. Site-specific labeling was achieved by attaching the fluorophore, N-[2-(1-maleimidyl)ethyl]-7-(diethylamino)coumarin-3-carboxamide (MDCC), to the protein through the sulfhydryl group of the cysteine moiety. Steady-state fluorescence studies of the MPBP-MDCC conjugate showed a change in the intensity of the signal upon addition of Pi. Calibration curves for Pi were constructed by relating the intensity of the fluorescence signal with the amount of analyte present in the sample. The sensing system was first developed and optimized on a spectrofluorometer using ml volumes of sample. It was then adapted to be used on a microtiter plate arrangement with microliter sample volumes. The system's versatility was finally proven by developing a fiber optic fluorescence-based sensor for monitoring Pi. In all three cases the detection limits for the analyte were in the sub-microMolar range. It was also demonstrated that the sensing system was selective for phosphate over other structurally-similar anions, paving the way for the design and development of a new family of biosensors utilizing the specific binding properties of periplasmic proteins. c2003 Elsevier B.V. All rights reserved.

NASA Program Fundamental Space Biology↗

Irrigation Modernization Task 4: Accelerating Energy Solutions (FY2022 Final Report)

This report offers insights on energy solutions for irrigation modernization that serve the needs of farmers as well as residents and industry in the local community. Solutions are found in the irrigation districts where local generation from renewable energy sources – solar, hydro, and wind – can be combined with energy storage and customer loads. These combined resources configured in microgrids can lower costs during peak loads and provide resiliency by maintaining electricity supply during outages. The goal of this project, as stated in the FY2022 AOP, is to promote realization of energy solutions that are tailored to physical location, community, infrastructure, and energy value streams. Further, it is to develop examples of how to increase value of, and overcome barriers to, energy solutions in the context of irrigation modernization. In pursuit of that goal, the project looked at options for: 1) Reducing the cost of energy consumed in irrigation systems, 2) Increasing the revenue from surplus power generation, and 3) Deploying new power generation configured as part of a local microgrid. Potential solutions to reducing energy costs and increasing surplus power revenue revolve around addressing regulatory and legal constraints tied to how power is purchased by and sold to the irrigator or irrigation district. Some headway was made in identifying barriers and ways to push utilities to be more accommodating to distributed energy sources; however, for the most part, real progress hinges on changes at the regulatory and legislative level. Deployment of local, renewable generation systems can be implemented provided the economics of the project and the location are favorable. In concert with Famers Conservation Alliance and Energy Trust of Oregon, a number of approaches were studied in the past year, including off-grid solar powered pumps, grid-tied community solar projects, and in-conduit canal hydropower systems. Ultimately three viable projects were identified: 1) North Unit Irrigation District/City of Redmond, Oregon Critical Facility Microgrid – offers combined in-conduit hydro and solar power generation. 2) Wallowa County/Joseph, Oregon Irrigation System Upgrades – centered on upgrades to a non-powered dam that will add a turbine as well as in-conduit power in canal feeders downstream. 3) Medford, Oregon Wastewater Treatment Plant Biogas Cogeneration System – centered on building out biogas storage and grid upgrades to power the plant, sell excess power, and provide emergency backup power (supplanting a diesel generator). Each of these projects has characteristics that broaden the understanding of the value of microgrids employing renewable energy to achieve resiliency and net-zero carbon goals. The first two projects are centered on new hydropower systems. Although the Medford project is only tangentially tied to an irrigation district, it was selected for study analysis as it was the only one mature enough (with sufficient data) to complete an analysis within this project year. Thus, we chose to move forward developing a case study, in concert with the Community Water-Power Resilience project, to demonstrate a method for evaluating such projects. Essentially, this case study serves as a template for studies to be carried out next year that more directly involve irrigation system hydropower, e.g., the project at the Wallowa County/Joseph, Oregon Irrigation System. Lastly, it is recognized that the locations and case studies in this report are all located in Oregon. We recognize this as a limitation. While the intent is not to ignore other states or regions, this result is driven by the fact that we have cultivated a collaboration with non-profit entities in Oregon that focus on these topics – Farmers Conservation Alliance and Energy Trust of Oregon. These partners were central to identifying projects that may be good fits for this program. A goal in the coming year is to establish collaboration with entities in other states/regions that, similarly, can connect us to potential projects in their geographic area. The potential benefits from the WPTO’s support for demonstration projects as energy solutions in irrigation districts include: (1) Alternative power supplies for communities and farms using renewable, carbon-free energy resources, (2) Cost savings for electricity for communities and farms, (3) Resiliency of power supplies for critical loads when electricity from the grid is not available, (4) Resiliency of power supplies for critical infrastructure in the event of catastrophic events, and (5) Demonstration of irrigation modernization projects that provide resilience and a reduced carbon footprint to irrigation districts and nearby communities. These deployments can serve as vanguards/archetypes spurring similar projects in other districts and states.

13 HYDRO ENERGY↗

Mechanistic Insights Revealed by YbtPQ in the Occluded State

Recently, several ATP-binding cassette (ABC) importers have been found to adopt the typical fold of type IV ABC exporters. Presumably, these importers would function under the transport scheme of “alternating access” like those exporters, cycling through inward-open, occluded, and outward-open conformations. Understanding how the exporter-like importers move substrates in the opposite direction requires structural studies on all the major conformations. To shed light on this, here we report the structure of yersiniabactin importer YbtPQ from uropathogenic Escherichia coli in the occluded conformation trapped by ADP-vanadate (ADP-Vi) at a 3.1 Å resolution determined by cryo-electron microscopy. The structure shows unusual local rearrangements in multiple helices and loops in its transmembrane domains (TMDs). In addition, the dimerization of the nucleotide-binding domains (NBDs) promoted by the vanadate trapping is highlighted by the “screwdriver” action at one of the two hinge points. These structural observations are rare and thus provide valuable information to understand the structural plasticity of the exporter-like ABC importers.

59 BASIC BIOLOGICAL SCIENCES↗

Temperature Evolution of the Activation Barriers Leads to Meyer−Neldel Rules for Structural Relaxation and Transport in Polymers

Understanding activation barriers controlling structural relaxation in glass-forming liquids, molecular transport, and ionic conductivity in amorphous polymers is a grand challenge of fundamental scientific and materials engineering interest across disciplines. Over decades, intriguing but puzzling empirical correlations between the elementary time scale of activated barrier crossing and the apparent Arrhenius activation energy, the so-called Meyer−Neldel (MN) rules, have been discovered in diverse liquids and glasses. Here, in this study, we formulate and successfully apply a new experimental analysis and an explicitly dynamical theoretical framework which provides an understanding of the origin, validity, and failure of such correlations, that bridge and unify the three fields of structural relaxation, molecular transport, and ionic conductivity in liquids and quenched glasses. Distinct quasi-universal laws are predicted in equilibrated liquids and nonequilibrium glasses, consistent with experiments. Our analysis reveals that even if the relaxation appears Arrhenius over a limited temperature range, the physical activation barrier is generally temperature-dependent in polymeric systems even below glass transition temperature. In addition, we show that the approximate validity of classical MN rules hinges on a linear temperature dependence of this barrier and the temperature range probed in experiments. Our findings are relevant for controlling the activation barrier in functional soft polymeric materials relevant to molecular separations, barrier coatings, and charge transport, and also provide new constraints on the theoretical understanding of the mechanism underlying slow activated dynamics in glass-forming condensed matter.

Meyer-Neldel rules↗

A standardized workflow for kinetic metabolic model curation and dissemination

Kinetic metabolic models provide invaluable insights into cellular metabolism, supporting applications in synthetic biology, metabolic engineering, and systems biology. However, reproducibility and utility of these models hinge on clear and rigorous documentation, standardized annotation, and accessible visualization. This paper presents a workflow for building, annotating, visualizing, and sharing kinetic metabolic models. Our method integrates community standards and open-source tools to ensure reproducibility, interoperability, and user accessibility. This procedure enables researchers to produce reusable and well-documented kinetic models, advancing their role as powerful tools in metabolic research.

Cook, Margaret [Univ. of Washington, Seattle, WA (↗

From broadband biphotons to frequency combs via spectral compression with time-varying cavities

Biphoton frequency combs are promising resources for quantum networking due in large part to their compatibility with the telecommunication infrastructure. Here, in this work, we propose a method to periodically compress broadband frequency-entangled photons into biphoton frequency combs by utilizing time-varying linear cavities. Our approach hinges on rapid modulation of the input cavity coupling, yielding high spectral purity in each output comb line similar to that achieved with narrowband filters, but without the associated loss in flux. We examine the dependence of spectral purity and compression on coupling strength, cavity loss, and switching speed, finding realistic regimes supporting purities in excess of 0.999 and peak enhancement factors of 100× and beyond.

Myilswamy, Karthik V. [Purdue Univ., West Lafayett↗

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗

Two polymorphs of [Rh(μ-I)(COD)] 2

The solid-state structure of di-μ-iodido-bis{[(1,2,5,6-η)-cycloocta-1,4-diene]rhodium(I)}, [Rh 2 I 2 (C 8 H 12 ) 2 ] or [Rh(μ-I)(COD)] 2 , was determined from two crystals with different morphologies, which were found to correspond to two polymorphs containing Rh dimers with significantly different molecular structures. Both polymorphs are monoclinic and the [Rh(μ-I)(COD)] 2 molecules in each case possess C 2 v symmetry. However, the core geometry of the butterfly-shaped Rh 2 I 2 core differs substantially. In the C 2/ c polymorph, the core geometry of [Rh(μ-I)(COD)] 2 B is bent, with a hinge angle of 96.13 (8)° and a Rh...Rh distance of 2.9612 (11) Å. The P 2 1 / c polymorph features a more planar [Rh(μ-I)(COD)] 2 P core geometry, with a hinge angle of 145.69 (9)° and a Rh...Rh distance of 3.7646 (5) Å.

36 MATERIALS SCIENCE↗

Identifying Human Errors and Error Mechanisms From Accident Reports Using Large Language Models

Emerging operational concepts for aviation hinge on novel paradigms for human machine interaction. Critical to their safe operation is early consideration of human error into the design process. Existing methods for consideration of human error require significant expert input, which is challenging both in early design and in novel systems for which there is little existing safety expertise. In this research, we propose a methodology for identifying human error, error producing factors, and mechanisms in early design from historical incident reports. Additionally, we hypothesize that cross-domain sharing of lessons learned can aid with early design human considerations in circumstances where data is not relevant or incomplete. This is addressed by identifying causes of human error in aviation and railway domains through applying state-of-the art natural language processing techniques to historical incident reports. Using this method, it is possible to extract extensive reports on human error from past incidents. Using the proposed approach, we identify nine human errors from railway reports and fourteen from aviation reports, with three errors common to both domains. There is at least one error producing conditions for each human error while a majority of the errors have more than one error mechanism. We also found that a majority of the human errors, error producing factors, and error mechanisms (even if they are not common between the domains) can be used to inform safe operations across domains as long as the errors are not domain specific and are interpreted and contextualized using engineering judgement.

Human Errors↗

Single-molecule reaction mapping uncovers diverse behaviours of electrocatalytic surface Pd–H intermediates

Many vital electrocatalytic transformations hinge on reactive surface metal–hydrogen intermediates (M–H*), yet the low concentration and transient nature of such intermediates present formidable challenges to in-depth investigation. Here we use single-molecule super-resolution reaction imaging to directly probe surface palladium–hydrogen (Pd–H*) intermediates on individual palladium nanocubes during electrocatalytic hydrogen evolution. Our approach visualizes hydrogen spillover from palladium to the surrounding substrate surface over hundreds of nanometres away and dissects substantial inter- and intraparticle heterogeneity. Through Gaussian-broadening kinetic analysis, we reveal that ensemble-averaged measurements systematically overestimate the stability of Pd–H*. Moreover, we resolve three subpopulations of palladium nanocubes with distinct reactivity features, uncovering critical correlations between intermediate stability, hydrogenation reactivity and transition-state properties. Finally, our findings highlight the necessity of single-particle resolution for capturing the intrinsic complexity of electrocatalysts; our approach is also broadly applicable to interrogate surface-reactive intermediates across a wide array of electrocatalytic pathways.

electrocatalysis↗

Aeroservoelastic tailoring for lateral control enhancement

The need for effective aileron power for aircraft lateral control and turning maneuvers dates back to the Wright Brothers and their wing warping concept for active stabilization of their aircraft. Early researchers in Great Britain, Japan, Germany and the United States explored ways to increase the effectiveness of control aileron to generate a roll moment. The basic problem of aileron effectiveness and the interrelationship between structural distortion and the loads applied by the control surface is illustrated. A rigid wing/aileron surface will develop the capability to generate increased roll rates as airspeed increases. A flexible surface will become less effective as airspeed increases because of the twisting distortion created by the aft-mounted control surface. This tendency is further worsened by bending distortion of an aft swept wing. This study focuses its attention on the ability of a combined effort between structural redesign of a wing and sizing and placement of a control surface to create specified roll performance with a minimum hinge moment. This design optimization problem indicates the advantages of simultaneous consideration of structural design and control design.

Weisshaar, Terrence A.↗

Molecular Coatings Improve the Selectivity and Durability of CO 2 Reduction Chalcogenide Photocathodes

The quest for solar-driven conversion of carbon dioxide to chemicals and fuels hinges upon the identification of an efficient, durable, and selective photocathode. Chalcogenide p-type semiconductors exemplified by chalcopyrite Cu(In,Ga)Se 2 (CIGS) have been effectively deployed as photocathodes. However, selectivity toward CO 2 reduction and durability of the commonly used CdS adlayer remain primary challenges. Here, we demonstrate that for the wide band gap CuGa 3 Se 5 chalcopyrite absorber these challenges are well addressed by an organic coating generated in situ from an N,N'-(1,4-phenylene)bispyridinium ditriflate salt in the electrolyte. The molecular additive provides a 30-fold increase in selectivity toward CO2R products compared to the unmodified system and lowers Cd corrosion at least 10-fold. This dual functionality highlights the promise of hybrid solid-state-molecular photocathodes for enabling durable and efficient solar fuel systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Actuator and aerodynamic modeling for high-angle-of-attack aeroservoelasticity

Accurate prediction of airframe/actuation coupling is required by the imposing demands of modern flight control systems. In particular, for agility enhancement at high angle of attack and low dynamic pressure, structural integration characteristics such as hinge moments, effective actuator stiffness, and airframe/control surface damping can have a significant effect on stability predictions. Actuator responses are customarily represented with low-order transfer functions matched to actuator test data, and control surface stiffness is often modeled as a linear spring. The inclusion of the physical properties of actuation and its installation on the airframe is therefore addressed using detailed actuator models which consider the physical, electrical, and mechanical elements of actuation. The aeroservoelastic analysis procedure is described in which the actuators are modeled as detailed high-order transfer functions and as approximate low-order transfer functions. The impacts of unsteady aerodynamic modeling on aeroservoelastic stability are also investigated by varying the order of approximation, or number of aerodynamic lag states, in the analysis. Test data from a thrust-vectoring configuration of an F/A-l8 aircraft are compared to predictions to determine the effects on accuracy as a function of modeling complexity.

Brenner, Martin J.↗

Roadmap for transforming heterogeneous catalysis with artificial intelligence

Artificial intelligence (AI) is poised to transform heterogeneous catalysis, opening avenues for catalytic materials discovery. By uncovering intricate patterns in high-dimensional data, AI has been reshaping our pursuit of sustainable catalytic processes across the energy, environmental and chemical sectors. This promise, however, hinges on overcoming fundamental barriers, including limitations in data availability and quality, challenges in the generalizability and interpretability of data-augmented decisions, and the persistent gap between in silico predictions and experiments. Furthermore, we outline a forward-looking roadmap for deeply integrating AI into heterogeneous catalysis with an AI-ready data ecosystem, multimodal foundation models, and ultimately autonomous laboratories to accelerate the development of next-generation catalytic technologies via AI-empowered human–machine collaboration.

Computational methods↗

Building spatial symmetries into parameterized quantum circuits for faster training

Abstract Practical success of quantum learning models hinges on having a suitable structure for the parameterized quantum circuit. Such structure is defined both by the types of gates employed and by the correlations of their parameters. While much research has been devoted to devising adequate gate-sets, typically respecting some symmetries of the problem, very little is known about how their parameters should be structured. In this work, we show that an ideal parameter structure naturally emerges when carefully considering spatial symmetries (i.e. the symmetries that are permutations of parts of the system under study). Namely, we consider the automorphism group of the problem Hamiltonian, leading us to develop a circuit construction that is equivariant under this symmetry group. The benefits of our novel circuitstructure, called ORB, are numerically probed in several ground-state problems. We find a consistent improvement (in terms of circuit depth, number of parameters required, and gradient magnitudes) compared to literature circuit constructions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Building spatial symmetries into parameterized quantum circuits for faster training

Practical success of quantum learning models hinges on having a suitable structure for the parameterized quantum circuit. Such structure is defined both by the types of gates employed and by the correlations of their parameters. While much research has been devoted to devising adequate gate-sets, typically respecting some symmetries of the problem, very little is known about how their parameters should be structured. In this work, we show that an ideal parameter structure naturally emerges when carefully considering spatial symmetries (i.e. the symmetries that are permutations of parts of the system under study). Namely, we consider the automorphism group of the problem Hamiltonian, leading us to develop a circuit construction that is equivariant under this symmetry group. The benefits of our novel circuitstructure, called ORB, are numerically probed in several ground-state problems. We find a consistent improvement (in terms of circuit depth, number of parameters required, and gradient magnitudes) compared to literature circuit constructions.

97 MATHEMATICS AND COMPUTING↗

Advanced eLectrical Bus (ALBus) CubeSat: From Build to Flight

The Advanced eLectrical Bus (ALBus) CubeSat project is a technology demonstration mission of a 3-U CubeSat with an advanced, digitally controlled electrical power system capability and novel use of Shape Memory Alloy (SMA) technology for reliable deployable solar array mechanisms. The objective of the project was to advance the state of power management and distribution (PMAD) capabilities to enable future missions requiring flexible and reliable power systems with higher output power capabilities. The goals of the mission were to demonstrate 100W distribution to a target electrical load, respond to continuous and fast transient power requirements, and show reliable deployment of solar arrays and antennas utilizing re-settable SMA mechanisms. The power distribution function of the ALBus PMAD system is unique in the total power to target load capability. Power is distributed from batteries to provide 100W of power directly to a resistive load. The deployable solar arrays utilize NASA Glenn Research Center’s Nickel-Titanium-Palladium-Platinum high-temperature SMAs for the retention and release mechanism, and a super-elastic binary NiTi alloy for the hinge component. The deployable solar array hinge design features the utilization of SMA material properties for a dual purpose. First, the hinge uses the super-elastic SMA properties to provide the spring force to deploy the arrays. Second, the electrical conductivity properties of the SMA enables the design to provide clean conduits for power transfer from the deployable arrays to the power management system. This eliminates the need for electrical harnesses between the arrays and the PMAD system in the ALBus system design. The uniqueness of the SMA retention and release mechanism design is the ability to reset the mechanism and reuse the same hardware. This allow functional tests of the mechanisms before flight with no degradation of performance and flying the hardware that is tested. The project launched as part of the CubeSat Launch Initiative Educational Launch of Nanosatellites (ELaNa) XIX mission on Rocket Lab’s Electron in December 2018. This paper summarizes the final launched design of ALBus and lessons learned from the technology and overall project from development through flight.

Deboshri Sadhukhan↗

Actuator and aerodynamic modeling for high-angle-of-attack aeroservoelasticity

Accurate prediction of airframe/actuation coupling is required by the imposing demands of modern flight control systems. In particular, for agility enhancement at high angle of attack and low dynamic pressure, structural integration characteristics such as hinge moments, effective actuator stiffness, and airframe/control surface damping can have a significant effect on stability predictions. Actuator responses are customarily represented with low-order transfer functions matched to actuator test data, and control surface stiffness is often modeled as a linear spring. The inclusion of the physical properties of actuation and its installation on the airframe is therefore addressed in this paper using detailed actuator models which consider the physical, electrical, and mechanical elements of actuation. The aeroservoelastic analysis procedure is described in which the actuators are modeled as detailed high-order transfer functions and as approximate low-order transfer functions. The impacts of unsteady aerodynamic modeling on aeroservoelastic stability are also investigated in this paper by varying the order of approximation, or number of aerodynamic lag states, in the analysis. Test data from a thrust-vectoring configuration of an F/A-18 aircraft are compared to predictions to determine the effects on accuracy as a function of modeling complexity.

Brenner, Martin J.↗