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At least 1,117 records · Page 62

Quantum paramagnetism in a non-Kramers rare-earth oxide: Monoclinic Pr 2 Ti 2 O 7

Little is so far known about the magnetism of the A 2 B 2 O 7 monoclinic layered perovskites that replace the spin-ice supporting pyrochlore structure for r A /r B > 1.78. We show that high quality monoclinic Pr 2 Ti 2 O 7 single crystals with a three-dimensional network of non-Kramers Pr 3+ ions that interact through edge-sharing superexchange interactions, form a singlet ground-state quantum paramagnet that does not undergo any magnetic phase transitions down to, at least, 1.8 K. The chemical phase stability, structure, and magnetic properties of the layered perovskite Pr 2 Ti 2 O 7 were investigated using x-ray diffraction, transmission electron microscopy, and magnetization measurements. Synthesis of polycrystalline samples with the nominal compositions of Pr 2 Ti 2+x O 7 (–0.16 ≤ x ≤ 0.16 ) showed that deviations from the Pr 2 Ti 2 O 7 stoichiometry lead to secondary phases of related structures including the perovskite phase Pr 2/3 TiO 3 and the orthorhombic phases Pr 4 Ti 9 O 24 and Pr 2 TiO 5 . No indications of site disordering (stuffing and antistuffing) or vacancy defects were observed in the Pr 2 Ti 2 O 7 majority phase. A procedure for growth of high-structural-quality stoichiometric single crystals of Pr 2 Ti 2 O 7 by the traveling solvent floating zone method is reported. Thermomagnetic measurements of single-crystalline Pr 2 Ti 2 O 7 reveal an isolated singlet ground state that we associate with the low-symmetry crystal electric-field environments that split the (2J + 1 = 9)-fold degenerate spin-orbital multiplets of the four differently coordinated Pr 3+ ions into 36 isolated singlets resulting in an anisotropic temperature-independent van Vleck susceptibility at low T. Here, a small isotropic Curie term is associated with 0.96(2)% noninteracting Pr 4+ impurities.

36 MATERIALS SCIENCE↗

Structural and dynamic changes associated with beneficial engineered single-amino-acid deletion mutations in enhanced green fluorescent protein

The beneficial engineered single-amino-acid deletion variants EGFP{sup D190Δ} and EGFP{sup A227Δ} have been studied. Single-amino-acid deletions are a common part of the natural evolutionary landscape but are rarely sampled during protein engineering owing to limited and prejudiced molecular understanding of mutations that shorten the protein backbone. Single-amino-acid deletion variants of enhanced green fluorescent protein (EGFP) have been identified by directed evolution with the beneficial effect of imparting increased cellular fluorescence. Biophysical characterization revealed that increased functional protein production and not changes to the fluorescence parameters was the mechanism that was likely to be responsible. The structure EGFP{sup D190Δ} containing a deletion within a loop revealed propagated changes only after the deleted residue. The structure of EGFP{sup A227Δ} revealed that a ‘flipping’ mechanism was used to adjust for residue deletion at the end of a β-strand, with amino acids C-terminal to the deletion site repositioning to take the place of the deleted amino acid. In both variants new networks of short-range and long-range interactions are generated while maintaining the integrity of the hydrophobic core. Both deletion variants also displayed significant local and long-range changes in dynamics, as evident by changes in B factors compared with EGFP. Rather than being detrimental, deletion mutations can introduce beneficial structural effects through altering core protein properties, folding and dynamics, as well as function.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Poly[guanidinium [tri-$\mu$-formato-$\kappa^6O:O'$- formato-$\kappa^2O,O'$yttrium( III )]]

In the title coordination polymer, {(CH 6 N 3 )[Y(CHO 2 ) 4 ]} n , the yttrium(III) ion is coordinated by one O,O-bidentate formate ion and six $\mu_2$ bridging formate ions, generating a square-antiprismatic YO8 coordination polyhedron. The bridging formate ions connect the metal ions into an anionic, three-dimensional network. Charge compensation is provided by guanidinium ions, which interact with the framework by way of N—H∙∙∙O hydrogen bonds. The guanidine molecules reside in porous channels of 3.612 by 8.189 Å, when considering the van der Waals radii of the nearest atoms (looking down the $\mathcal{a}$-axis).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

All in the timing: epigenetic control of greening

During germination, the emerging seedling relies on a limited supply of energy and nutrients stored within itself and the seed. This often occurs underground in darkness where seedlings undergo skotomorphogenesis, characterized by hypocotyl elongation, reduced root growth, and small closed cotyledons forming an apical hook to protect the shoot apical meristem as the seedling grows though the soil towards sunlight. Such long and pale dark-grown seedlings are commonly referred to as etiolated (from the French étiolier (to make pale)). However, a seedling must eventually find sunlight and make an irreversible shift to photoautotrophic growth (photomorphogenesis or de-etiolation). This leads to a dramatic change in physiology, including reduced hypocotyl elongation, increased root growth, expansion and unfolding of the cotyledons, and the biogenesis of photosynthetic plastids (i.e. chloroplasts). Furthermore, this shift is accompanied by a massive change in gene expression, with about one-third of genes being reprogrammed. A large amount of the transcriptional response is regulated by the plant photoreceptors (phytochromes and cryptochromes) that activate transcriptional networks. Furthermore, this involves the rapid degradation of PHYTOCHROME INTERACTING FACTORS (PIFs), which are basic helix-loop-helix domain-containing transcription factors that repress photomorphogenesis in the dark.

59 BASIC BIOLOGICAL SCIENCES↗

Synthesis, Structure, and Fluorescence of a Novel Cadmium Compound

A novel cadmium compound, [(CdI{sub 3}){sub 2}(μ{sub 2}-I)]{sub 2}(Me{sub 2}-4,4'-H{sub 2}bipy){sub 3} (1) (Me = methyl; 4,4'-bipy = 4,4'-bipyridine) with the Me{sub 2}-4,4'-H{sub 2}bipy moiety generated in situ, has been prepared through a solvothermal reaction and structurally characterized by X-ray single crystal diffraction analysis. Compound 1 is characterized by an isolated structural motif, consisting of [(CdI{sub 3}){sub 2}(μ{sub 2}-I)]{sup 3–} anions and Me{sub 2}-4,4'-H{sub 2}bipy{sup 2+} cations. The [(CdI{sub 3}){sub 2}(μ{sub 2}-I)]{sup 3–} anions and Me{sub 2}-4,4'-H{sub 2}bipy{sup 2+} cations interconnect together via C–H···I hydrogen-bonding interactions to complete a three-dimensional (3D) supramolecular network. Solid state fluorescent spectrum reveals an emission band in the violet region.

36 MATERIALS SCIENCE↗

An opinion-driven behavioral dynamics model for addictive behaviors

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual’s behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Additionally, individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters provide targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. Furthermore, this has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Using Digital Trace Data to Identify Regions and Cities

A greater understanding of human dynamics as they play out in both physical space and through inter-personal communication is vital for the design and development of intelligent and resilient cities. Physical context provides insight in to the space-time distribution of population and their activity patterns, while inter-personal communication can, for the first time, be measured at scale through virtual interactions. The confluence of these two enables spatial social network analysis in the built environment for edge computing, knowledge discovery, and artificial intelligence activities. In this work, we propose a novel method to discover such dynamics. We use a dataset of 72 million tweets to develop a spatially embedded network of communication, and then use community detection algorithms to explore regional and urban delineation in the United States. We find that the broad spatial delineation of communities and community sub-structure is consistent with major United States socio-cultural regions, states, and major metropolitan areas. We describe how these methods could be extended to generate a measure of socially cohesive regions that can be consistently applied anywhere there is a sufficiently rich data source. We hope the proposed methods will generate new perspectives on smart and resilient cities.

Brelsford, Christa↗

Exploring soybean metabolic pathways based on probabilistic graphical model and knowledge-based methods

Soybean (Glycine max) is a major source of vegetable oil and protein for both animal and human consumption. The completion of soybean genome sequence led to a number of transcriptomic studies (RNA-seq), which provide a resource for gene discovery and functional analysis. Several data-driven (e.g., based on gene expression data) and knowledge-based (e.g., predictions of molecular interactions) methods have been proposed and implemented. In order to better understand gene relationships and protein interactions, we applied probabilistic graphical methods, based on Bayesian network and knowledgebase constraints using gene expression data to reconstruct soybean metabolic pathways. The results show that this method can predict new relationships between genes, improving on traditional reference pathway maps.

54 ENVIRONMENTAL SCIENCES↗

Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics

We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec) to refer to biological sequences in general with protein-vectors (ProtVec) for proteins (amino-acid sequences) and gene-vectors (GeneVec) for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics. In the present paper, we focus on protein-vectors that can be utilized in a wide array of bioinformatics investigations such as family classification, protein visualization, structure prediction, disordered protein identification, and protein-protein interaction prediction. In this method, we adopt artificial neural network approaches and represent a protein sequence with a single dense n-dimensional vector. To evaluate this method, we apply it in classification of 324,018 protein sequences obtained from Swiss-Prot belonging to 7,027 protein families, where an average family classification accuracy of 93%±0.06% is obtained, outperforming existing family classification methods. In addition, we use ProtVec representation to predict disordered proteins from structured proteins. Two databases of disordered sequences are used: the DisProt database as well as a database featuring the disordered regions of nucleoporins rich with phenylalanine-glycine repeats (FG-Nups). Using support vector machine classifiers, FG-Nup sequences are distinguished from structured protein sequences found in Protein Data Bank (PDB) with a 99.8% accuracy, and unstructured DisProt sequences are differentiated from structured DisProt sequences with 100.0% accuracy. These results indicate that by only providing sequence data for various proteins into this model, accurate information about protein structure can be determined. Importantly, this model needs to be trained only once and can then be applied to extract a comprehensive set of information regarding proteins of interest. Moreover, this representation can be considered as pre-training for various applications of deep learning in bioinformatics.

Science & Technology - Other Topics↗

Systems biology markup language (SBML) level 3 package: multistate, multicomponent and multicompartment species, version 1, release 2

Rule-based modeling is an approach that permits constructing reaction networks based on the specification of rules for molecular interactions and transformations. These rules can encompass details such as the interacting sub-molecular domains and the states and binding status of the involved components. Conceptually, fine-grained spatial information such as locations can also be provided. Through “wildcards” representing component states, entire families of molecule complexes sharing certain properties can be specified as patterns. This can significantly simplify the definition of models involving species with multiple components, multiple states, and multiple compartments. The systems biology markup language (SBML) Level 3 Multi Package Version 1 extends the SBML Level 3 Version 1 core with the “type” concept in the Species and Compartment classes. Therefore, reaction rules may contain species that can be patterns and exist in multiple locations. Multiple software tools such as Simmune and BioNetGen support this standard that thus also becomes a medium for exchanging rule-based models. This document provides the specification for Release 2 of Version 1 of the SBML Level 3 Multi package. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the correction of errata and the addition of clarifications.

59 BASIC BIOLOGICAL SCIENCES↗

An Investigation into the Effects of Interface Stress and Interfacial Arrangement on Temperature Dependent Thermal Properties of a Biological and a Biomimetic Material

A significant effort in the biomimetic materials research is on developing materials that can mimic and function in the same way as biological tissues, on bio-inspired electronic circuits, on bio-inspired flight structures, on bio-mimetic materials processing, and on structural biomimetic materials, etc. Most structural biological and biomimetic material properties are affected by two primary factors: (1) interfacial interactions between an organic and an inorganic phase usually in the form of interactions between an inorganic mineral phase and organic protein network; and (2) structural arrangement of the constituents. Examples are exoskeleton structures such as spicule, nacre, and crustacean exoskeletons. A significant effort is being directed towards making synthetic biomimetic materials based on a manipulation of the above two primary factors. The proposed research is based on a hypothesis that in synthetic materials with biomimetic morphology thermal conductivity, k, (how fast heat is carried away) and thermal diffusivity, D, (how fast a material’s temperature rises: proportional to the ratio of k and heat capacity) can be engineered to be either significantly low or significantly high based on a combination of chosen interface orientation and interfacial arrangement in comparison to conventional material microstructures with the same phases and phase volume fractions. METHOD DEVELOPMENT 1. We have established a combined Raman spectroscopy and nanomechanical loading based experimental framework to perform environment (liquid vs. air vs. vacuum) dependent and temperature dependent (~1000 degree-C) in-situ thermal diffusivity measurements in biomaterials at nanoscale to micron scale along with the corresponding analytical theoretic calculations. (Zhang and Tomar, 2013) 2. We have also established a new classical molecular simulation based framework to measure thermal diffusivity in biomolecular interfaces. We are writing a publication currently (Qu and Tomar, 2013) to report the framework and findings in tropocollagen-hydroxyapatite based idealized biomaterial interfaces. PHYSICAL FINDINGS 1. Analyses using experiments have revealed that in the case of bone thermal conductivity and thermal diffusivity at micron scale shows significant dependence on compressive stress and temperature. Overall, there is a decrease with respect to increase in temperature and increase with respect to increase in compressive stress. Bio-molecular simulations on idealized tropocollagen-hydroxyapatite interfaces confirm such findings. However, simulations also reveal that thermal diffusivity and thermal conductivity can be significantly tailored by interfacial orientation. More importantly, in inorganic materials, interfaces contribute to reduce thermal conductivity and diffusivity. However, analyses here reveal that both can be increased despite presence of a lot of interfaces. 2. Based on significant role played by interfaces in affecting bone thermal properties, a crustacean-exoskeleton system is examined for thermal diffusivity using the newly developed setup. Special emphasis here is on this system since such arrangement is found to be common in fresh water shrimp as well as in some deep water organisms surviving in environment extremes. Experiments reveal that in such system thermal diffusivity is highly tailorable. 3. Overall, experiments and models have established that in biomaterial interfaces a counterintuitive role of interfaces in mediating thermal conduction as a function of stress and temperature is possible in contrast to inorganic materials where interfaces almost always lead to reduction of thermal conductivity as a function of such factors. More investigations are underway to reveal physical origins of such counter-physical characteristics. Such principles can be significantly useful in developing new and innovative bioenergy and inorganic energy systems where heat dissipation significantly affects system performance.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring Dark Sector Physics in MicroBooNE with e+e- Final States

Neutrinos are the second most abundant massive particle in the universe, but because of their small mass and weak interactions with matter, they are still not well understood. Due to their pervasive nature and unique properties, neutrinos make great probes to explore fundamental questions about the universe such as what is the composition of dark matter? The MiniBooNE experiment, designed to study neutrino oscillations, detected what has become a longstanding anomaly – an excess of low energy electromagnetic events from accelerator neutrino interactions. A possible explanation of the anomaly comes from neutrino interactions with nuclei that create heavier, sterile neutrinos that will decay quickly into electron-positron pairs. Complementing this is the MicroBooNE experiment, a liquid argon time projection chamber, that can reconstruct events well in both two and three dimensions and can distinguish electrons from photons. This reconstruction ability enables us to select dark sector neutrino interactions from other possible interactions using machine learning techniques such as graph neural networks (GNNs) which is the primary focus of this project.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The DSN programming system

The Deep Space Network programming system is described by a heuristic model. Interaction with two elements of that system, anomaly reporting and the MBASIC (trademark) language, is described in detail. Feedback from anomaly reporting indicates that the methodology resulted in a low anomaly rate and thereby also provided positive feedback. The need to reduce operating costs prompted the implementation of the MBASIC (trademark) language as a compiler.

Irvine, A. P.↗

ADAMS: AIRLAB data management system user's guide

The AIRLAB Data Management System (ADAMS) is an online environment that supports research at NASA's AIRLAB. ADAMS provides an easy to use interactive interface that eases the task of documenting and managing information about experiments and improves communication among project members. Data managed by ADAMS includes information about experiments, data sets produced, software and hardware available in AIRLAB as well as that used in a particular experiment, and an on-line engineer's notebook. The User's Guide provides an overview of the ADAMS system as well as details of the operations available within ADAMS. A tutorial section takes the user step-by-step through a typical ADAMS session. ADAMS runs under the VAX/VMS operating system and uses the ORACLE database management system and DEC/FMS (the Forms Management System). ADAMS can be run from any VAX connected via DECnet to the ORACLE host VAX. The ADAMS system is designed for simplicity, so interactions within the underlying data management system and communications network are hidden from the user.

Conrad, C. L.↗

Cyberinfrastructure for Airborne Sensor Webs

Since 2004 the NASA Airborne Science Program has been prototyping and using infrastructure that enables researchers to interact with each other and with their instruments via network communications. This infrastructure uses satellite links and an evolving suite of applications and services that leverage open-source software. The use of these tools has increased near-real-time situational awareness during field operations, resulting in productivity improvements and the collection of better data. This paper describes the high-level system architecture and major components, with example highlights from the use of the infrastructure. The paper concludes with a discussion of ongoing efforts to transition to operational status.

Freudinger, Lawrence C.↗

Cyberinfrastructure for Aircraft Mission Support

Forth last several years NASA's Airborne Science Program has been developing and using infrastructure and applications that enable researchers to interact with each other and with airborne instruments via network communications. Use of these tools has increased near realtime situational awareness during field operations, resulting it productivity improvements, improved decision making, and the collection of better data. Advances in pre-mission planning and post-mission access have also emerged. Integrating these capabilities with other tools to evolve coherent service-oriented enterprise architecture for aircraft flight and test operations is the subject of ongoing efforts.

Freudinger, Lawrence C.↗

Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions

Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper.

Luxhoj, J. T.↗

Recent Advances in Discrete Crack Modeling Applied to Laminated Composites with Emphasis on: Floating Node Method, VCCT and Cohesive Zone Modeling

The present talk will provide an overview of the work performed during the Advanced Composites Project (ACP) on the development, and verification and validation of the Floating Node Method (FNM) as well as the Virtual Crack Closure Technique (VCCT) and cohesive zone modeling (CZM). The FNM is a finite element-based technique to represent crack networks. The complex nature of matrix crack-delamination interactions observed in unidirectional (UD) tape laminates suggests that a methodology such as the FNM method may be required to be able to accurately simulate damage progression in these laminates. Simulating crack onset and growth within the context of the FNM relies on techniques such as VCCT and CZM. The talk is organized to provide, via select examples, an overview of the breadth of the Verification & Validation (V&V) exercises performed during the ACP, and how these challenged the state-of-the art and guided further developments in discrete crack modeling, while helping to establish confidence in the progress made and map the challenges ahead. The performance of the VCCT and CZM individually, and in combination with the FNM can be assessed through verification exercises. These exercises typically consist of a comparison of simulation results to known numerical or analytical solutions. Verification is key to identify implementation issues and limitations that, otherwise, may remain undetected and cloud any subsequent validation efforts. Indeed, a subset of these numerical exercises led to further developments of the VCCT and the FNM method as will be illustrated. Before embarking on the subsequent validation of the framework, it is critical to have adequate characterization data. However, the testing campaign conducted revealed material responses that challenged the state-of-the-art and required further developments. The developments in CZM technology associated with the modeling of the responses of hybrid interfaces (fabric/UD) will be given as an example. Finally, the talk will conclude with a summary of the validation exercises performed under quasi-static and fatigue loadings, highlighting some of the key achievements, outstanding challenges and lessons learned.

finite elements↗