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At least 631 records · Page 35

Biology Inspired Approach for Communal Behavior in Sensor Networks

Research in wireless sensor network technology has exploded in the last decade. Promises of complex and ubiquitous control of the physical environment by these networks open avenues for new kinds of science and business. Due to the small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors working in concert. Although the reduction in size has been phenomenal it results in severe limitations on the computing, communicating, and power capabilities of these devices. Under these constraints, research efforts have concentrated on developing techniques for performing relatively simple tasks with minimal energy expense assuming some form of centralized control. Unfortunately, centralized control does not scale to massive size networks and execution of simple tasks in sparsely populated networks will not lead to the sophisticated applications predicted. These must be enabled by new techniques dependent on local and autonomous cooperation between sensors to effect global functions. As a step in that direction, in this work we detail a technique whereby a large population of sensors can attain a global goal using only local information and by making only local decisions without any form of centralized control.

Jones, Kennie H.↗

How production networks amplify economic growth

Technological improvement is the most important cause of long-term economic growth. In standard growth models, technology is treated in the aggregate, but an economy can also be viewed as a network in which producers buy goods, convert them to new goods, and sell the production to households or other producers. We develop predictions for how this network amplifies the effects of technological improvements as they propagate along chains of production, showing that longer production chains for an industry bias it toward faster price reduction and that longer production chains for a country bias it toward faster growth. These predictions are in good agreement with data from the World Input Output Database and improve with the passage of time. The results show that production chains play a major role in shaping the long-term evolution of prices, output growth, and structural change.

99 GENERAL AND MISCELLANEOUS↗

Selective CO 2 Reduction by Bis(bipyridine)cobalt(II) Catalysts: The Role of Pendant Pyridine as a Proton Acceptor

Electrochemical CO 2 reduction reaction (CO 2 RR) catalyzed by molecular earth-abundant metal catalysts is a promising strategy to convert CO 2 into value-added products. One recent trend in this field has been focusing on the rational design of catalysts by incorporating redox-active ligands and modifying the secondary coordination sphere (SCS) to achieve efficient and selective CO 2 RR. Herein, we report a series of Co bis­(bipyridine) catalysts featuring various dangling groups, such as pyridine, tertiary amine, or butyl, in the secondary coordination sphere (Co-PyMe, Co-Py, Co-PrN, and Co-Bu). Efficient, selective electrocatalytic CO 2 RR was achieved by the complexes after the generation of triply reduced intermediate consisting of a Co I center and a dianionic ligand, producing CO as the major product and trace amount of H 2 . Strong correlations with the identity of dangling groups and turnover frequency (TOF) have been observed, in which Co-PyMe displayed the highest TOF (1086 s –1 in MeCN/H 2 O). Mechanistic studies indicated that the acceleration of CO 2 RR with pyridine-functionalized catalysts were derived from the protonation of pyridine dangling groups which participated as weak acids in the H-bonding network with exogenous proton sources, stabilizing CO 2 -bound intermediates and facilitating proton transfer. In addition, precatalytic CO 2 binding and activation at the third reduction (−2.1 V) was revealed by CV and SEC-IR studies. The resultant doubly reduced CO-bound species acted as a trapping state which inhibited CO 2 RR electrocatalysis. Regeneration of active species was accessed via reductive dissociation of CO at a more negative potential. In conclusion, this study highlights the combined effects of redox-active ligands and pyridine/pyridinium as SCS groups on CO 2 RR catalysis and provides design principles for future development of CO 2 RR catalysts utilizing pyridine/pyridiniums as SCS functional groups to fine-tune the catalytic activity.

CO2 reduction↗

Fe-single-atom catalyst nanocages linked by bacterial cellulose-derived carbon nanofiber aerogel for Li-S batteries

Li-S battery (LSB) is promising for achieving high capacity. Still, its development is hindered by the complex redox process with sluggish kinetics and particularly the resulting lithium polysulfides (LiPS) shuttle effects. Single-atom catalysts (SACs), with their maximized atom utilization, could effectively chemisorb soluble LiPSs and expedite the sulfide conversion reaction kinetics. Here we report incorporating Fe single metal atom catalyst (Fe-SAC) in the sulfur cathode design and its electrocatalytic effects. Fe-doped ZIF-8 nanocages were introduced into a cheap biomass bacteria cellulose. A pyrolysis process converted them into an aerogel structure with Fe-SAC-functionalized N-doped carbon nanocages linked by a carbon nanofiber network (FeSA-NC@CBC), which was applied as a scaffold to fabricate freestanding and binder-free sulfur cathodes. He we conducted electrochemical measurements to reveal Fe-SAC functions including lowering energy barriers for S 8 reduction to liquid-phase LiPSs and further to solid-phase Li 2 S 2 /Li 2 S and accelerating Li 2 S 2 /Li 2 S nucleation and deposition, as corroborated by our theoretical calculation results. Benefiting from the synergistic effects of highly active Fe-SAC and three-dimensional conductive network, the sulfide reaction kinetics is improved, which can diminish LiPS shuttle effects and therefore improve LBS rate performance and cycling stability. Accordingly, the fabricated FeSA-NC@CBC composite cathode delivers an excellent rate capability at 2C with a reversible capacity of 840 mAh/g and a long-term cyclic stability of 800 mAh/g at 1C after 500 cycles.

25 ENERGY STORAGE↗

Overexpression of miR-133 decrease primary endothelial cells proliferation and migration via FGFR1 targeting

Highlights: • FGFR1 signaling can bring about angiogenesis in cancer. • Through downregulating FGFR1, miR-133 caused reductions in bFGF activity. • Reduced bFGF activity result in diminished proliferation and migratory ability of ECs. • Overexpression of miR-133 could reduce the rate of cell division. • MiR-133 could disturb capillary network formation of transfected ECs as well. Angiogenesis is one of the essential hallmarks of cancer that is controlled by the balance between positive and negative regulators. FGFR1 signaling is crucial for the execution of bFGF-induced proliferation, migration, and tube formation of endothelial cells (ECs) and onset of angiogenesis on tumors. The purpose of this study is to identify whether or not miR-133 regulates FGFR1 expression and accordingly hypothesize if it plays a crucial role in modulating bFGF/FGFR1 activity in ECs and blocking tumor angiogenesis through targeting FGFR1. The influences of miR-133 overexpression on bFGF stimulated endothelial cells were assessed by cell growth curve, MTT assaying, tube formation, and migration assays. Forced expression of miR-133 caused significant reductions in bFGF-induced proliferation and migratory ability of ECs. MiR-133 Expression was negatively correlated with both mRNA and protein levels of FGFR1 in the transfected ECs isolated from peripheral blood. Moreover, overexpression of miR-133 drastically reduced the rate of cell division and disturbed capillary network formation of transfected ECs. These findings suggest that miR-133 plays an important function in bFGF-induced angiogenesis processes in ECs and provides a rationale for new therapeutic approaches to suppress tumor angiogenesis and cancer.

60 APPLIED LIFE SCIENCES↗

Tandem synthesis of tetrahydroquinolines and identification of the reaction network by operando NMR

The study of the reaction mechanism and complex network for heterogeneously catalyzed tandem reactions is challenging but can guide reaction design and optimization. Here, we describe a case study using bifunctional metal–organic framework supported Pd nanoparticles (Pd/UiO-66(HCl)) for the one-pot tandem synthesis of substituted tetrahydroquinolines via the Claisen–Schmidt condensation and reductive intramolecular cyclization. The directly observed evolution of intermediates and products, including reactive species containing hydroxylamine group and unstable intermediate 2-phenyl-3,4-dihydroquinoline, was enabled by operando magic angle spinning nuclear magnetic resonance studies under 50 bar H 2 . The reaction network of the tandem reaction is deduced based on reaction kinetic information obtained from the operando study. The optimized procedure was applied to various acetophenone and nitrobenzaldehyde derivatives carrying different functional groups, and eight valuable substituted tetrahydroquinolines were obtained in moderate to good yields. This work provides a molecular-level understanding of the catalytic system and brings up new opportunities for efficient and sustainable synthesis of medicinally relevant building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selective reduction of CO to acetaldehyde with CuAg electrocatalysts

Electrochemical CO reduction can serve as a sequential step in the transformation of CO 2 into multicarbon fuels and chemicals. In this study, we provide insights on how to steer selectivity for CO reduction almost exclusively toward a single multicarbon oxygenate by carefully controlling the catalyst composition and its surrounding reaction conditions. Under alkaline reaction conditions, we demonstrate that planar CuAg electrodes can reduce CO to acetaldehyde with over 50% Faradaic efficiency and over 90% selectivity on a carbon basis at a modest electrode potential of −0.536 V vs. the reversible hydrogen electrode. The Faradaic efficiency to acetaldehyde was further enhanced to 70% by increasing the roughness factor of the CuAg electrode. Density functional theory calculations indicate that Ag ad-atoms on Cu weaken the binding energy of the reduced acetaldehyde intermediate and inhibit its further reduction to ethanol, demonstrating that the improved selectivity to acetaldehyde is due to the electronic effect from Ag incorporation. These findings will aid in the design of catalysts that are able to guide complex reaction networks and achieve high selectivity for the desired product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

59 BASIC BIOLOGICAL SCIENCES↗

A physics-constrained neural network for multiphase flows

The present study develops a physics-constrained neural network (PCNN) to predict sequential patterns and motions of multiphase flows (MPFs), which includes strong interactions among various fluid phases. To predict the order parameters, which locate individual phases in the future time, a neural network (NN) is applied to quickly infer the dynamics of the phases by encoding observations. The multiphase consistent and conservative boundedness mapping algorithm (MCBOM) is next implemented to correct the predicted order parameters. This enforces the predicted order parameters to strictly satisfy the mass conservation, the summation of the volume fractions of the phases to be unity, the consistency of reduction, and the boundedness of the order parameters. Then, the density of the fluid mixture is updated from the corrected order parameters. Finally, the velocity in the future time is predicted by another NN with the same network structure, but the conservation of momentum is included in the loss function to shrink the parameter space. The proposed PCNN for MPFs sequentially performs (NN)-(MCBOM)-(NN), which avoids nonphysical behaviors of the order parameters, accelerates the convergence, and requires fewer data to make predictions. Numerical experiments demonstrate that the proposed PCNN is capable of predicting MPFs effectively.

Mechanics↗

Reconfigurations in Brain Networks Upon Awakening From Slow Wave Sleep: Interventions and Implications in Neural Communication

Sleep inertia is the brief period of impaired alertness and performance experienced immediately after waking. Little is known about the neural mechanisms underlying this phenomenon. A better understanding of the neural processes during sleep inertia may offer insight into the awakening process. We observed brain activity every 15 min for 1 hr following abrupt awakening from slow wave sleep during the biological night. Using 32-channel electroencephalography, a network science approach, and a within-subject design, we evaluated power, clustering coefficient, and path length across frequency bands under both a control and a polychromatic short-wavelength-enriched light intervention condition. We found that under control conditions, the awakening brain is typified by an immediate reduction in global theta, alpha, and beta power. Simultaneously, we observed a decrease in the clustering coefficient and an increase in path length within the delta band. Exposure to light immediately after awakening ameliorated changes in clustering. Our results suggest that long-range network communication within the brain is crucial to the awakening process and that the brain may prioritize these long-range connections during this transitional state. Our study highlights a novel neurophysiological signature of the awakening brain and provides a potential mechanism by which light improves performance after waking.

EEG↗

Synchrotron micro-computed tomography analysis of neutron-irradiated U-Mo fuel

The three-dimensional (3D) microstructure of neutron-irradiated uranium-10 wt.% molybdenum (U-10Mo) fuel with a burn-up of 9.8 × 10 21 fissions/cm 3 was characterized using a novel, multi-modal synchrotron micro-computed tomography approach combining propagation-based phase-contrast enhanced and absorption contrast techniques. The porosity development, porosity interconnectedness, swelling, composition, local thickness of the zirconium (Zr) diffusion barrier, and the influence of the fuel–cladding interaction on the local composition and pore morphology, were uniquely determined in 3D. Two cuboids were produced using a focused ion beam-scanning electron microscope at the Zr diffusion barrier–fuel interface and in the bulk fuel. The bulk fuel sample swelled by 53.3 [+9.7/−3.1]%, while the fuel near the Zr–fuel interface swelled by 63.3 [+14.7/−7.2]%. The average local thickness of the Zr diffusion barrier decreased by 53 %, compared to the expected pre-irradiated thickness. Four pore morphology regions were identified initiating parallel to the fuel–Zr interaction region: (1) an interaction layer of suppressed porosity, (2) a layer of elongated and interconnected porosity, (3) a transition zone of low porosity, and (4) a layer of unoriented porosity representative of the bulk fuel behavior. The increase in porosity near the diffusion barrier corresponded to a higher U concentration compared to that in the bulk fuel. The interconnected porosity in the fuel near the diffusion barrier was extensive and oriented parallel to the diffusion barrier, while the bulk fuel had more compact and isolated pore networks. The interaction layer, despite having suppressed porosity, was nearly 100 wt.% U. Porosity suppression at the diffusion barrier corresponds to the expected reduction in radiation-driven diffusion of Xe at the interface despite the anticipated increase in fission product nucleation originating from a higher U concentration. In conclusion, the novel 3D insights of the porosity, swelling, and compositional variations characterized herein can improve the fidelity of fuel performance codes for proliferation-resistant fuels for research and test reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Electronic and Quantum Transport Properties of Substitutionally Doped Double-Walled Carbon Nanotubes

A first-principles investigation of the electronic and quantum transport properties of double-walled carbon nanotubes doped with nitrogen and boron atoms is presented. Concentric nanotube sidewalls separated by the typical graphitic van der Waals bond distance are found to strongly interact upon incorporation of doping atoms in the hexagonal networks. The local perturbation caused by the doping atoms extends over both shells due to a hybridization of their electronic states, yielding a reduction of the backscattering efficiency as compared with two independent single-walled nanotubes. A multiscale approach for the study of transport properties of micrometer-long double-walled carbon nanotubes demonstrates that transitions from the ballistic to the localized regime can occur depending on the type of doping and the energy of the charge carrier. These results shed light on the quantum mechanism by which B and N doping represent an efficient method to create mobility gaps in metallic concentric carbon nanotubes.

Lopez-Bezanilla, Alejandro↗

Hierarchical Transactive Control of Flexible Building Loads Under Distribution LMP

With grid modernization efforts, future distribution networks, which consist of various distributed generators and flexible loads, will be more flexible and active. All new network components of distributed energy resources (DERs) drive and enable the transition towards a market-based distribution net-work that seeks the optimal allocation of all DERs. To address challenges associated with DERs, one promising solution is to utilize demand-side flexibility of building loads facilitated by demand response (DR) programs and provide ancillary grid services through distribution-level markets. Under this new paradigm, this paper proposes an efficient DR management strategy incorporating emerging price signals of distribution markets, i.e., distribution locational marginal price (DLMP), based on a hierarchical transactive control approach. The proposed approach establishes a two-layer decision-making framework; the upper layer formulates a bilevel model to obtain an optimal demand response (ODR) under DLMP, and the lower layer employs model-free control to dispatch the (aggregated) ODR to individual end users. Numerical case studies using a modified IEEE 33 test network are performed to verify the effectiveness of the proposed approach; load shifting and peak shaving for the distribution system operator and payments’ reduction for end users while maintaining their comfort.

Park, Byungkwon↗

Performance Evaluation of Gray-box and Machine Learning Models of a Thermal Energy Storage System with Active Insulation

An interior partition wall integrated with active thermal storage and a dynamic insulation system was built and then installed in an office building in Oak Ridge, Tennessee, TN. This smart wall, termed the Empower Wall, was equipped with embedded pipes in the building envelope core component and an additional pipe network enclosing rigid insulation to switch on and off the active insulation dynamically. The performance of the wall's contribution to cooling load reduction under different parameters has been investigated in previous publications. Aiming to be deployed into model predictive control and other optimization methods, simplified and reliable models for the developed wall and the room accommodating it are required. They are needed to characterize the properties and thermal response of both Empower Wall and building envelope, which form an essential component for accurate indoor temperature or cooling/heating demand prediction. In this study, simplified gray-box and regression models as well as machine learning model were developed and the performance of them were compared and analyzed.

Cui, Borui↗

Fault-Tolerant Local-Area Network

Local-area network (LAN) for computers prevents single-point failure from interrupting communication between nodes of network. Includes two complete cables, LAN 1 and LAN 2. Microprocessor-based slave switches link cables to network-node devices as work stations, print servers, and file servers. Slave switches respond to commands from master switch, connecting nodes to two cable networks or disconnecting them so they are completely isolated. System monitor and control computer (SMC) acts as gateway, allowing nodes on either cable to communicate with each other and ensuring that LAN 1 and LAN 2 are fully used when functioning properly. Network monitors and controls itself, automatically routes traffic for efficient use of resources, and isolates and corrects its own faults, with potential dramatic reduction in time out of service.

Morales, Sergio↗

Capacity and interference in a PCS system

In order to increase the capacity of a Personal Communication Service (PCS) system, the PCS system environment needs to be understood. The PCS system environment is briefly described in this paper. Because the frequency reuse concept is used to increase the capacity of PCS, the cochannel cells created cause cochannel interference. There are two approaches to reduce cochannel interference. One is the microcell approach (within the existing system) and the other is the reduction of cochannel cell separation approach (developing a new system). In-building communications using PCS systems has been addressed. Also, the Intelligent Network (IN) is described to show its importance. The cellular system has great potential to be the future PCS system.

Lee, William C. Y.↗

Wake Vortex Advisory System (WakeVAS) Evaluation of Impacts on the National Airspace System

This report is one of a series that describes an ongoing effort in high-fidelity modeling/simulation, evaluation and analysis of the benefits and performance metrics of the Wake Vortex Advisory System (WakeVAS) Concept of Operations being developed as part of the Virtual Airspace Modeling and Simulation (VAMS) project. A previous study, determined the overall increases in runway arrival rates that could be achieved at 12 selected airports due to WakeVAS reduced aircraft spacing under Instrument Meteorological Conditions. This study builds on the previous work to evaluate the NAS wide impacts of equipping various numbers of airports with WakeVAS. A queuing network model of the National Airspace System, built by the Logistics Management Institute, Mclean, VA, for NASA (LMINET) was used to estimate the reduction in delay that could be achieved by using WakeVAS under non-visual meteorological conditions for the projected air traffic demand in 2010. The results from LMINET were used to estimate the total annual delay reduction that could be achieved and from this, an estimate of the air carrier variable operating cost saving was made.

Smith, Jeremy C.↗