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At least 1,153 records · Page 64

Distinct cellular expression and subcellular localization of Kv2 voltage‐gated K + channel subtypes in dorsal root ganglion neurons conserved between mice and humans

Abstract The distinct organization of Kv2 voltage‐gated potassium channels on and near the cell body of brain neurons enables their regulation of action potentials and specialized membrane contact sites. Somatosensory neurons have a pseudounipolar morphology and transmit action potentials from peripheral nerve endings through axons that bifurcate to the spinal cord and the cell body within ganglia including the dorsal root ganglia (DRG). Kv2 channels regulate action potentials in somatosensory neurons, yet little is known about where Kv2 channels are located. Here, we define the cellular and subcellular localization of the Kv2 paralogs, Kv2.1 and Kv2.2, in DRG somatosensory neurons with a panel of antibodies, cell markers, and genetically modified mice. We find that relative to spinal cord neurons, DRG neurons have similar levels of detectable Kv2.1 and higher levels of Kv2.2. In older mice, detectable Kv2.2 remains similar, while detectable Kv2.1 decreases. Both Kv2 subtypes adopt clustered subcellular patterns that are distinct from central neurons. Most DRG neurons co‐express Kv2.1 and Kv2.2, although neuron subpopulations show preferential expression of Kv2.1 or Kv2.2. We find that Kv2 protein expression and subcellular localization are similar between mouse and human DRG neurons. We conclude that the organization of both Kv2 channels is consistent with physiological roles in the somata and stem axons of DRG neurons. The general prevalence of Kv2.2 in DRG as compared to central neurons and the enrichment of Kv2.2 relative to detectable Kv2.1 in older mice, proprioceptors, and axons suggest more widespread roles for Kv2.2 in DRG neurons.

Neurosciences & Neurology↗

Structure‐Aware Representation Learning for Effective Performance Prediction

ABSTRACT Application performance is a function of several unknowns stemming from the interactions between the application, runtime, OS, and underlying hardware, making it challenging to model performance using deep learning techniques, especially without a large labeled dataset. Collecting such labeled longitudinal datasets can take weeks. Intuitively, developers could save analysis time during code development by taking a comparative approach between multiple applications. However, the unknown dynamic interactions between applications and execution environments make it difficult for deep learning‐based models to predict the performance of new applications. In this paper, we address these problems by presenting a labeled dataset for the community and taking a comparative analysis approach to explore the source code differences between different correct implementations of the same problem. This paper assesses the feasibility of using purely static information, for example, Abstract Syntax Tree (AST), of applications to predict performance change based on code structure. We evaluate several deep learning‐based representation learning techniques for source code and propose an architecture for the tree‐based Long Short‐Term Memory (LSTM) models to discover latent representations for a source code's hierarchical structure. We demonstrate that our proposed architecture enables feed‐forward predictive models to predict change in performance using source code with up to 84% accuracy.

Ramadan, Tarek [Department of Computer Science Tex↗

The Role of Lewis Acid Sites in γ-Al 2 O 3 Oligomerization

Olefin oligomerization by γ-Al 2 O 3 has recently been reported, and it was suggested that Lewis acid sites are catalytic. The goal of this study is to determine the number of active sites per gram of alumina to confirm that Lewis acid sites are indeed catalytic. Addition of an inorganic Sr oxide base resulted in a linear decrease in the propylene oligomerization conversion at loadings up to 0.3 wt %; while, there is a >95 % loss in conversion above 1 wt % Sr. Additionally, there was a linear decrease in the intensity of the Lewis acid peaks of absorbed pyridine in the IR spectra with an increase in Sr loading, which correlates with the loss in propylene conversion, suggesting that Lewis acid sites are catalytic. Characterization of the Sr structure by XAS and STEM indicates that single Sr 2+ ions are bound to the γ-Al 2 O 3 surface and poison one catalytic site per Sr ion. The maximum loading needed to poison all catalytic sites, assuming uniform surface coverage, was ~0.4 wt % Sr, giving an acid site density of ~0.2 sites per nm2 of γ-Al 2 O 3 , or approximately 3 % of the alumina surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Persistence of Methionine Side Chain Mobility at Low Temperatures in a Nine‐Residue Low Complexity Peptide, as Probed by 2 H Solid‐State NMR

Abstract Methionine side chains are flexible entities which play important roles in defining hydrophobic interfaces. We utilize deuterium static solid‐state NMR to assess rotameric inter‐conversions and other dynamic modes of the methionine in the context of a nine‐residue random‐coil peptide (RC9) with the low‐complexity sequence GGKGMGFGL. The measurements in the temperature range of 313 to 161 K demonstrate that the rotameric interconversions in the hydrated solid powder state persist to temperatures below 200 K. Removal of solvation significantly reduces the rate of the rotameric motions. We employed 2 H NMR line shape analysis, longitudinal and rotation frame relaxation, and chemical exchange saturation transfer methods and found that the combination of multiple techniques creates a significantly more refined model in comparison with a single technique. Further, we compare the most essential features of the dynamics in RC9 to two different methionine‐containing systems, characterized previously. Namely, the M35 of hydrated amyloid‐β 1–40 in the three‐fold symmetric polymorph as well as Fluorenylmethyloxycarbonyl (FMOC)‐methionine amino acid with the bulky hydrophobic group. The comparison suggests that the driving force for the enhanced methionine side chain mobility in RC9 is the thermodynamic factor stemming from distributions of rotameric populations, rather than the increase in the rate constant.

Vugmeyster, Liliya↗

Converting Second‐Order Saddle Points to Transition States: New Principles for the Design of 4π Photoswitches

Abstract Molecular photoswitches have demonstrated potential for storing solar energy at the molecular level, with power densities comparable to commercial batteries and hydroelectric energy storage. However, development of efficient photoswitches is hindered by limitations in cyclability and optical properties of existing materials. We here demonstrate that certain limitations in photoswitches based on electrocyclizations stem from the issue of controlling competition between Woodward‐Hoffmann allowed and forbidden pathways. Our approach moves beyond the traditional view of activation barriers and reveals that second‐order saddle points are crucial in dictating the competition between disrotatory and conrotatory pathways. These insights suggest new opportunities to manipulate the competition between these pathways through geometric constraints, fundamentally altering the connectivity of the potential energy surface. Our study also emphasizes the necessity of multi‐reference methods and the need to conduct higher‐dimensional explorations for competing pathways beyond photoswitch design.

Chemistry↗

Disturbance-accelerated succession increases the production of a temperate forest

Many secondary deciduous forests of eastern North America are approaching a transition in which maturing early successional tree species are declining, resulting in an uncertain future for these forests’ century-long carbon (C) sink. We initiated the Forest Accelerated Succession Experiment (FASET) at the University of Michigan Biological Station to examine the patterns and mechanisms underlying forest C cycling following the stem-girdling induced mortality of >6,700 early successional Populus spp. (aspen) and Betula papyrifera (paper birch). Since 2008, meteorological flux tower-based C cycling observations from the 33-ha treatment forest have been paired with those from a nearby unmanipulated forest. Following over a decade of observations, herein we revisit our core hypothesis: that net ecosystem production (NEP) would increase following the transition to mid-late successional species dominance due to increased canopy structural complexity. Supporting our hypothesis, NEP was stable, briefly declined, and then increased relative to the control in the decade following disturbance; however, increasing NEP was not associated with rising structural complexity but rather the rapid 1-year recovery of total LAI as mid-late successional Acer, Quercus, and Pinus assumed canopy dominance. The transition to mid-late successional species dominance improved carbon-use efficiency (CUE = NEP/gross primary production) as ecosystem respiration declined. Similar soil respiration rates in control and treatment forests, along with species differences in leaf physiology and the rising relative growth rates of mid-late successional species in the treatment forest, suggest changes in aboveground plant respiration and growth, respectively, were primarily responsible for increases in NEP. We conclude that deciduous forests transitioning from early to middle succession are capable of sustained or increased NEP, even when experiencing extensive tree mortality. This adds to mounting evidence that aging deciduous forests in the region will function as C sinks for decades to come.

54 ENVIRONMENTAL SCIENCES↗

Carbon cycling across ecosystem succession in a north temperate forest: Controls and management implications

Despite decades of progress, much remains unknown about successional trajectories of carbon (C) cycling in north temperate forests. Drivers and mechanisms of these changes, including the role of different types of disturbances, are particularly elusive. To address this gap, we synthesized decades of data from experimental chronosequences and long-term monitoring at a well-studied, regionally representative field site in northern Michigan, USA. Our study provides a comprehensive assessment of changes in above- and belowground ecosystem components over two centuries of succession, links temporal dynamics in C pools and fluxes with underlying drivers, and offers several conceptual insights to the field of forest ecology. Our first advance shows how temporal dynamics in some ecosystem components are consistent across severe disturbances that reset succession and partial disturbances that slightly modify it: both of these disturbance types increase soil N availability, alter fungal community composition, and alter growth and competitive interactions between short-lived pioneer and longer-lived tree taxa. Further, these changes in turn affect soil C stocks, respiratory emissions, and other belowground processes. Second, we show that some other ecosystem components have effects on C cycling that are not consistent over the course of succession. For example, canopy structure does not influence C uptake early in succession but becomes important as stands develop, and the importance of individual structural properties changes over the course of two centuries of stand development. Third, we show that in recent decades, climate change is masking or overriding the influence of community composition on C uptake, while respiratory emissions are sensitive to both climatic and compositional change. In synthesis, we emphasize that time is not a driver of C cycling; it is a dimension within which ecosystem drivers such as canopy structure, tree and microbial community composition change. Changes in those drivers, not in forest age, are what control forest C trajectories, and those changes can happen quickly or slowly, through natural processes or deliberate intervention. Stemming from this view and a whole-ecosystem perspective on forest succession, we offer management applications from this work and assess its broader relevance to understanding long-term change in other north temperate forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Uncertainty in inventories for life cycle assessment: State‐of‐the‐art, challenges, and new technologies

Uncertainty is a critical factor that can hinder the quality and potential applications of life cycle assessment (LCA) results. A prominent source of uncertainty stems from the life cycle inventory (LCI) data. Various methodologies exist to estimate the uncertainty associated with LCI data, primarily based on the widely used structured pedigree matrix approach or the computationally intensive Monte Carlo simulation. This perspective review explores how new technologies (e.g., computational algorithms and data collection methods) from data science and related fields can contribute to identifying, quantifying, and reducing uncertainty in LCI modeling. A brief overview of the sources of uncertainty in LCI modeling and how they are addressed in current LCA practice is provided. Additionally, several new technologies are identified, and the potential benefits of their implementation in reducing uncertainties in LCI modeling are discussed. This perspective review concludes by identifying potential areas that require further development for these technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Advancing river corridor science beyond disciplinary boundaries with an inductive approach to catalyse hypothesis generation

Abstract A unified conceptual framework for river corridors requires synthesis of diverse site‐, method‐ and discipline‐specific findings. The river research community has developed a substantial body of observations and process‐specific interpretations, but we are still lacking a comprehensive model to distill this knowledge into fundamental transferable concepts. We confront the challenge of how a discipline classically organized around the deductive model of systematically collecting of site‐, scale‐, and mechanism‐specific observations begins the process of synthesis. Machine learning is particularly well‐suited to inductive generation of hypotheses. In this study, we prototype an inductive approach to holistic synthesis of river corridor observations, using support vector machine regression to identify potential couplings or feedbacks that would not necessarily arise from classical approaches. This approach generated 672 relationships linking a suite of 157 variables each measured at 62 locations in a fifth order river network. Eighty four percent of these relationships have not been previously investigated, and representing potential (hypothetical) process connections. We document relationships consistent with current understanding including hydrologic exchange processes, microbial ecology, and the River Continuum Concept, supporting that the approach can identify meaningful relationships in the data. Moreover, we highlight examples of two novel research questions that stem from interpretation of inductively‐generated relationships. This study demonstrates the implementation of machine learning to sieve complex data sets and identify a small set of candidate relationships that warrant further study, including data types not commonly measured together. This structured approach complements traditional modes of inquiry, which are often limited by disciplinary perspectives and favour the careful pursuit of parsimony. Finally, we emphasize that this approach should be viewed as a complement to, rather than in place of, more traditional, deductive approaches to scientific discovery.

54 ENVIRONMENTAL SCIENCES↗

High‐throughput combinatorial approach expedites the synthesis of a lead‐free relaxor ferroelectric system

Abstract Developing novel lead‐free ferroelectric materials is crucial for next‐generation microelectronic technologies that are energy efficient and environment friendly. However, materials discovery and property optimization are typically time‐consuming due to the limited throughput of traditional synthesis methods. In this work, we use a high‐throughput combinatorial synthesis approach to fabricate lead‐free ferroelectric superlattices and solid solutions of (Ba 0.7 Ca 0.3 )TiO 3 (BCT) and Ba(Zr 0.2 Ti 0.8 )O 3 (BZT) phases with continuous variation of composition and layer thickness. High‐resolution x‐ray diffraction (XRD) and analytical scanning transmission electron microscopy (STEM) demonstrate high film quality and well‐controlled compositional gradients. Ferroelectric and dielectric property measurements identify the “optimal property point” achieved at the composition of 48BZT–52BCT. Displacement vector maps reveal that ferroelectric domain sizes are tunable by varying {BCT–BZT} N superlattice geometry. This high‐throughput synthesis approach can be applied to many other material systems to expedite new materials discovery and properties optimization, allowing for the exploration of a large area of phase space within a single growth. image

36 MATERIALS SCIENCE↗

Multilayered Network Models for Security: Enhancing System Security Engineering with Orchestration

Security engineering approaches can often focus on a particular domain—physical security, cyber security, or personnel security, for example. Yet, security systems engineering consistently faces challenges requiring socio-technical solutions to address evolving and dynamic complexity. While some drivers of this complexity stem from complex risk environments, innovative adversaries, and disruptive technologies, other drivers are endogenous and emerge from the interactions across security engineering approaches. In response, INCOSE's Systems Security Working Group identified the need to better coordinate “disparate security solutions [that] operate independently” as one of eleven key concepts in their IS21 FuSE Security Roadmap. From this perspective, this need for “security orchestration” aligns with the perspective that security is a property that emerges from interactions within complex systems. Current efforts at Sandia National Laboratories are developing a systems security engineering approach that describes high consequence facility (HCF) security as a multidomain set of interacting layers. The result is a multilayered network (MLN)-based approach that captures the interactions between infrastructure, physical components, digital components, and humans in nuclear security systems. This article will summarize the MLN-based approach to HCF security and describe two preliminary results demonstrating potential benefits from incorporating interactions across disparate security solutions. Here, leveraging the logical structure of networks, this MLN model-based approach provides an example of how security orchestration provides enhanced systems security engineering solutions.

42 ENGINEERING↗

Using pollen in turbidites for vegetation reconstructions

Turbidites, deposited by sub-aqueous gravity flows, are common in sedimentary archives worldwide and present a unique challenge and opportunity when reconstructing past vegetation through pollen analysis. When sampling pollen from a sediment core for palaeovegetation records, it is common practice to target background sediments (i.e. pelagic sediment) and avoid sampling turbidites, as they are presumed to portray a misleading picture of past vegetation. This assumption stems from our limited understanding of pollen abundance and distribution through turbidites, meaning that palynologists overlook deposits that could potentially be used to reconstruct past vegetation and climate. We present pollen assemblage and sedimentological data from four recent (<150 years) deep marine turbidite deposits from the Hikurangi Subduction Margin, Aotearoa-New Zealand, with the aim of understanding the abundance and distribution of pollen in fine-grained turbidites. We find that pollen is diluted in the bases of turbidites, but despite this dilution, the proportions of different pollen taxa remain consistent through each turbidite. These results confirm that pollen can be sampled from turbidites for palaeovegetation reconstructions and that sampling the fine-grained upper parts of turbidites will provide the best pollen recovery.

59 BASIC BIOLOGICAL SCIENCES↗

Investigation of Corrosion Behavior of Carbide Phase Strengthened Nickel‐Based Alloy in Molten Fluoride Salt

The corrosion behavior of a high creep strength carbide-phase strengthened Ni-based alloy in molten FLiNaK (LiF-NaF-KF: 46.5-11.5-42 mol%) salt in the temperature range of 700°C–750°C has been investigated as a part of the development of structural alloys for fluoride salt-based molten salt reactors (MSRs). The alloy composition was designed based on Hastelloy-N, but with the goal of improving creep strength. Cr depletion depth, a measure of corrosion, was observed to be single micrometers after several hundred hours of corrosion testing. Sequential corrosion testing involving testing of pre-tested samples in fresh salt coupled with SEM-EDS, scanning transmission electron microscopy (STEM) examinations and thermodynamic and kinetic modeling, suggest that the corrosion rate at the alloy-salt interface is governed by diffusion of elements from the alloy bulk to the surface. The carbide phases in the corrosion-tested sample microstructure were identified to be largely M 6 C-type Mo-rich carbides and MC-type mixed carbides. Atom probe tomography (APT) showed some partitioning of Cr and Ti to the carbide phase and showed the carbide phases to be stable at the salt-facing surface.

Gordon, Ryan [Univ. of Wisconsin, Madison, WI (Uni↗

Demonstrating Hierarchical System Development With the Common Community Physics Package Single‐Column Model: A Case Study Over the Southern Great Plains

This study demonstrates a specific application of the hierarchical system development (HSD) approach to investigate, analyze, and attribute model issues within the Unified Forecast System (UFS), with a focus on process isolation. By evaluating a non‐precipitating, shallow cumulus case at the Atmospheric Radiation Measurement Southern Great Plains site in the UFS global forecast against the observation, the investigation identifies a warmer and deeper daytime convective planetary boundary layer (PBL) and misrepresented nocturnal PBL transition. Hypothesis testing, which employs the Common Community Physics Package (CCPP) single‐column model (SCM) and uses the same physics as the UFS global model, confirms that these issues are attributed to the model physics and initialization. Specifically, misrepresented PBL processes are linked to problematic surface condition and a lack of cloud formation, which may stem from deficiencies in PBL and cloud microphysics parameterizations and their interactions. The UFS initial condition contributes to an earlier, excessively collapsed daytime convective boundary layer and a lack of decoupling between the stable boundary layer and residual layer late in the afternoon. This work introduces an avenue for the community to engage with the application of HSD, along with the CCPP and CCPP SCM, to understand the interplay of model physics, disentangle the roles of model components, as well as facilitate model and forecast improvement.

54 ENVIRONMENTAL SCIENCES↗

On the perturbation effect and LET dependence of beam quality correction factors in carbon ion beams

Background: In a recent study, we reported beam quality correction factors, f Q , in carbon ion beams using Monte Carlo (MC) methods for a cylindrical and a parallel-plate ionization chamber (IC). A non-negligible perturbation effect was observed; however, the magnitude of the perturbation correction due to the specific IC subcomponents was not included. Furthermore, the stopping power data presented in the International Commission on Radiation Units and Measurements (ICRU) report 73 were used, whereas the latest stopping power data have been reported in the ICRU report 90. Purpose: The aim of this study was to extend our previous work by computing f Q correction factors using the ICRU 90 stopping power data and by reporting IC-specific perturbation correction factors. Possible energy or linear energy transfer (LET) dependence of the f Q correction factor was investigated by simulating both pristine beams and spread-out Bragg peaks (SOBPs). Methods: The TOol for PArticle Simulation (TOPAS)/GEANT4 MC code was used in this study. A 30 × 30 × 50 cm 3 water phantom was simulated with a uniform 10 × 10 cm 2 parallel beam incident on the surface. A Farmer-type cylindrical IC (Exradin A12) and two parallel-plate ICs (Exradin P11 and A11) were simulated in TOPAS using the manufacturer-provided geometrical drawings. The f Q correction factor was calculated in pristine carbon ion beams in the 150–450 MeV/u energy range at 2 cm depth and in the middle of the flat region of four SOBPs. The k Q correction factor was calculated by simulating the f Qo correction factor in a 60 Co beam at 5 cm depth. The perturbation correction factors due to the presence of the individual IC subcomponents, such as the displacement effect in the air cavity, collecting electrode, chamber wall, and chamber stem, were calculated at 2 cm depth for monoenergetic beams only. Additionally, the mean dose-averaged and track-averaged LET was calculated at the depths at which the f Q was calculated. Results: The ICRU 90 f Q correction factors were reported. The p dis correction factor was found to be significant for the cylindrical IC with magnitudes up to 1.70%. The individual perturbation corrections for the parallel-plate ICs were <1.0% except for the A11 p cel correction at the lowest energy. The f Q correction for the P11 IC exhibited an energy dependence of >1.00% and displayed differences up to 0.87% between pristine beams and SOBPs. Conversely, the f Q for A11 and A12 displayed a minimal energy dependence of <0.50%. The energy dependence was found to manifest in the LET dependence for the P11 IC. A statistically significant LET dependence was found only for the P11 IC in pristine beams only with a magnitude of <1.10%. Conclusions: The perturbation and k Q correction factor should be calculated for the specific IC to be used in carbon ion beam reference dosimetry as a function of beam quality.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Achieving Productivity to Recover and Restore Columbia River Stream-Type Chinook Salmon Relies on Increasing Smolt-To-Adult Survival

Abstract We analyzed and compared productivity and survival rates of populations of stream-type Chinook Salmon Oncorhynchus tshawytscha from the upper and middle ranges of their distribution in the Columbia River basin. These two groups of populations undergo vastly different exposures during migration through the Federal Columbia River Power System (FCRPS). Declines of the Snake River populations, listed as threatened under the U.S. Endangered Species Act, have been associated with the development and operation of the FCRPS. In contrast, John Day River stream-type Chinook Salmon populations, which were less affected by the FCRPS, have declined to a lesser extent and are not listed. Smolt-to-adult survival rates (SARs) accounted for a majority of the variation in life cycle survival rates of Snake River Chinook Salmon. Productivity declined to 13% and 44% of historical productivity levels for Snake River and John Day River populations, respectively. A synthesis of previous studies contrasting anthropogenic impacts between the two regions supports the conclusion that FCRPS impacts explain the large difference in population productivity. Our results suggest that SARs of 4% would result in an expected productivity of up to 70% of historical levels (a SAR level consistent with regional restoration objectives). The SARs have been shown to be highly influenced by conditions within the FCRPS (e.g., water velocity and passage through dam powerhouses). Marine conditions also influence SARs; however, meaningful management actions are only available to affect conditions within the FCRPS. Given the importance of SARs to overall life cycle productivity, recovery and restoration strategies need to prioritize actions that have potential to substantially increase SARs by addressing the significant impacts of main-stem dams. This study highlights the importance of considering river management options in the face of increasingly variable and warming ocean conditions.

Petrosky, Charles E.↗

A Poromechanical Framework for Internal Interactions Induced by Solid Inclusions

The framework of poromechanics is generalized to simulate the multiscale behavior of porous media subjected to internal loadings stemming from the growth of solid inclusions. This generalization is designed to enable the study of anisotropic internal stress generation from solid growth within the pores, while recovering isotropic fluid-induced loading as a particular case. For this purpose, a mathematical strategy to define constitutive tensors in a thermodynamically consistent form is proposed, thus offering new opportunities for determining the poromechanical properties of a porous solid through advanced experimentation or micromechanical models. The framework is specialized by means of established elastic solutions for single pore–matrix interaction, as well as through homogenization schemes considering the interaction among congruent pores. In particular, the second Eshelby solution and the Tanaka–Mori–Benveniste homogenization scheme are used to derive a microporoelastic model. At an elemental scale, the model is tested under mixed control conditions by replicating different scenarios of geomaterial testing. In addition, the model characteristics are outlined with reference to inelastic microscopic loadings replicating chemo-mechanical forcing, such as expansive crystal formation. Through a series of parametric analyses, it is shown that the microstructure of the pores significantly influences the properties of porous media. Most notably, it is shown that the effects of a solid forming within the pores depend in a highly nonlinear fashion on the constitutive characteristics of the inhomogeneities and can therefore not be readily quantified or predicted without models capturing the diverse multiscale interactions among pores, inhomogeneities, and matrix.

chemomechanics↗