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At least 559 records · Page 31

Efficient Training of Deep Neural Operator Networks via Randomized Sampling

Neural operators (NOs) employ deep neural networks to learn the mappings between infinitedimensional function spaces. Deep operator network (DeepONet), a popular NO architecture, has demonstrated success in the real-time prediction of complex dynamics across various scientific and engineering applications. In this work, we introduce a random sampling technique to be adopted during the training of DeepONet, aimed at improving the generalization ability of the model, while significantly reducing the computational time. The proposed approach targets the trunk network of the DeepONet model that outputs the basis functions corresponding to the spatiotemporal locations of the bounded domain on which the physical system is defined. While constructing the loss function, DeepONet training traditionally considers a uniform grid of spatiotemporal points at which all the output functions are evaluated for each iteration. This approach leads to a larger batch size, resulting in poor generalization and increased memory demands, due to the limitations of the stochastic gradient descent (SGD) optimizer. The proposed random sampling over the inputs of the trunk net mitigates these challenges, improving generalization and reducing the memory requirements during training, resulting in significant computational gains. We validate our hypothesis through three benchmark examples, demonstrating substantial reductions in training time while achieving comparable or lower overall test errors relative to the traditional training approach. Our results indicate that incorporating randomization in the trunk network inputs during training enhances the efficiency and robustness of DeepONet, offering a promising avenue for improving the framework’s performance in modeling complex physical systems.

Karumuri, Sharmila [Department of Civil & Systems ↗

Challenges and Opportunities in State‐of‐the‐Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles

Extracellular vesicles (EVs) are membrane-bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept.

Dakup, Panshak P. [Pacific Northwest National Labo↗

Neural-network model for force prediction in multi-principal-element alloys

Atomistic simulations can provide useful insights into the physical properties of multi-principal-element alloys. However, classical potentials mostly fail to capture key quantum (electronic-structure) effects. Here we present a deep 3D convolutional neural network (3D CNN) based framework combined with a voxelization technique to design interatomic potentials for chemically complex alloys. We highlight the performance of the 3D CNN model and its efficacy in computing potentials using the medium-entropy alloy TaNbMo. In order to provide insights into the effect of voxel resolution, we implemented two approaches based on the inner and outer bounding boxes. An efficient 3D CNN model, which is as accurate as the density-functional theory (DFT) approach, for calculating potentials will provide a promising schema for accurate atomistic simulations of structure and dynamics of general multi-principle element alloys.

36 MATERIALS SCIENCE↗

Structures of drug-specific monoclonal antibodies bound to opioids and nicotine reveal a common mode of binding

Opioid-related fatal overdoses have reached epidemic proportions. Because existing treatments for opioid use disorders offer limited long-term protection, accelerating the development of newer approaches is critical. Monoclonal antibodies (mAbs) are an emerging treatment strategy that targets and sequesters selected opioids in the bloodstream, reducing drug distribution across the blood-brain barrier, thus preventing or reversing opioid toxicity. We previously identified a series of murine mAbs with high affinity and selectivity for oxycodone, morphine, fentanyl, and nicotine. To determine their binding mechanism, we used X-ray crystallography to solve the structures of mAbs bound to their respective targets, to 2.2 Å resolution or higher. Structural analysis showed a critical convergent hydrogen bonding mode that is dependent on a glutamic acid residue in the mAbs’ heavy chain and a tertiary amine of the ligand. Further, characterizing drug-mAb complexes represents a significant step toward rational antibody engineering and future manufacturing activities to support clinical evaluation.

60 APPLIED LIFE SCIENCES↗

Site-specific electronic structure of covalently linked bimetallic dyads from nitrogen K-edge x-ray absorption spectroscopy

A nitrogen K-edge x-ray absorption near-edge structure (XANES) survey is presented for tetrapyrido[3,2-a:',3'-c:3'',2''-h:2''',3'''-j]phenazine (tpphz)-bridged bimetallic assemblies that couple chromophore and catalyst transition metal complexes for light driven catalysis, as well as their individual molecular constituents. We demonstrate the high N site sensitivity of the N pre-edge XANES features, which are energetically well-separated for the phenazine bridge N atoms and for the individual metal-bound N atoms of the inner coordination sphere ligands. By comparison with the time-dependent density functional theory calculated spectra, we determine the origins of these distinguishable spectral features. We find that metal coordination generates large shifts toward higher energy for the metal-bound N atoms, with increasing shift for 3d < 4d < 5d metal bonding. This is attributed to increasing ligand-to-metal σ donation that increases the effective charge of the bound N atoms and stabilizes the N 1s core electrons. In contrast, the phenazine bridge N pre-edge peak is found at a lower energy due to stabilization of the low energy electron accepting orbital localized on the phenazine motif. While no sensitivity to ground state electronic coupling between the individual molecular subunits was observed, the spectra are sensitive to structural distortions of the tpphz bridge. Here these results demonstrate N K-edge XANES as a local probe of electronic structure in large bridging ligand motifs, able to distinctly investigate the ligand-centered orbitals involved in metal-to-ligand and ligand-to-ligand electron transfer following light absorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Unitarity-Limit Expansion for Two Nucleons with Perturbative Pions: Digest and Ideas

Theorists love nontrivial fixed points. In the Unitarity Limit, the NN 𝑆-wave binding energies are zero, the scattering lengths infinite, Physics is universal, i.e. insensitive to details of the interactions, and observables display richer symmetries, namely invariance under both scaling and Wigner’s combined SU(4) transformation of spin and isospin. In “Pionless” EFT, both are explicitly but weakly broken and hence perturbative in the Unitarity Window (phase shifts 45° ≲ δ(k) ≲ 135°, i.e. momenta k≈mπ). This Unitarity Expansion provides strong hints that Nuclear Physics resides indeed in a sweet spot: bound weakly enough to be insensitive to the details of the nuclear interaction; and therefore interacting strongly enough that the NN scattering lengths are perturbatively close to the Unitarity Limit. In this paradigm change, NN details are less important than NNN interactions to explain the complexity and patterns of the nuclear chart. This presentation is a digest of the first quantitative exploration of corrections to this picture when pions are included [1] (see there for a more comprehensive list of references). Since the pion mass and decay constant introduce dimensionful scales in the NN system, they explicitly break the symmetries of the Unitarity fixed point. In χEFT, these symmetries must therefore be hidden and instead be classified as emergent.

Griesshammer, Harald W. [The George Washington Uni↗

Structures of a phycobilisome in light-harvesting and photoprotected states

Phycobilisome (PBS) structures are elaborate antennae in cyanobacteria and red algae 1,2 . These large protein complexes capture incident sunlight and transfer the energy through a network of embedded pigment molecules called bilins to the photosynthetic reaction centres. However, light harvesting must also be balanced against the risks of photodamage. A known mode of photoprotection is mediated by orange carotenoid protein (OCP), which binds to PBS when light intensities are high to mediate photoprotective, non-photochemical quenching 3-6 . Here we use cryogenic electron microscopy to solve four structures of the 6.2 MDa PBS, with and without OCP bound, from the model cyanobacterium Synechocystis sp. PCC 6803. The structures contain a previously undescribed linker protein that binds to the membrane-facing side of PBS. For the unquenched PBS, the structures also reveal three different conformational states of the antenna, two previously unknown. The conformational states result from positional switching of two of the rods and may constitute a new mode of regulation of light harvesting. Further, only one of the three PBS conformations can bind to OCP, which suggests that not every PBS is equally susceptible to non-photochemical quenching. In the OCP-PBS complex, quenching is achieved through the binding of four 34kDa OCPs organized as two dimers. The complex reveals the structure of the active form of OCP, in which an approximately 60Å displacement of its regulatory carboxy terminal domain occurs. Finally, by combining our structure with spectroscopic properties 7 , we elucidate energy transfer pathways within PBS in both the quenched and light-harvesting states. Collectively, our results provide detailed insights into the biophysical underpinnings of the control of cyanobacterial light harvesting. The data also have implications for bioengineering PBS regulation in natural and artificial light-harvesting systems.

59 BASIC BIOLOGICAL SCIENCES↗

Multi-Objective design of interlocking metasurfaces using conditional diffusion models

Unit cell design remains a major challenge for interlocking metasurfaces, a promising joining technology for dissimilar materials, due to the complex, competing, multivariate design space and the need for rapid adaptation to varying performance requirements. This study explores Conditional Diffusion Models as a design optimization tool for interlocking metasurfaces. Given the complex, competing, multivariate design space for interlocking metasurfaces, unit cell design remains a major challenge for this joining technology. We trained a conditional diffusion model on 25,000 finite element analysis-simulated interlocking metasurface unit cells to generate designs with tailored thermo-mechanical properties (tensile strength, shear strength, and thermal conductivity) based on specified performance criteria. The model demonstrated a success rate of approximately 72 % in producing designs that met specified property bounds. The conditional diffusion model generated both thermally resistive and conductive designs, revealing clear trends in design characteristics: taller, dendritic structures were advantageous for tensile loads, while shorter, robust designs excelled in shear applications. Our findings indicate that the model's performance is more influenced by the breadth of the design space than by the quantity of training data, highlighting the importance of expansive design domains for generating innovative solutions. This work establishes conditional diffusion models as a highly efficient and adaptable tool for rapid interlocking metasurface unit cell design, paving the way for advancements in multi-material joining technologies, as well as highlighting the justification to leverage conditional diffusion models as design tools across complex design domains.

Conditional diffusion models↗

Collaborative Research: Natural Organic Matter and Microbial Controls on Mobilization/Immobilization of I and Pu in Soils and Waters Affected by Radionuclide Releases in USA and Japan

In this project, the relationship between natural organic matter (NOM) and two radioactive elements that are relevant to nuclear waste disposal were studied: Plutonium (Pu) and Iodine. The human and environmental risks associated with Pu stem mainly from the very long half-lives of several of its isotopes ( 238 Pu, 88 yr; 239 Pu, 24,100 yr; 240 Pu, 6560 yr) and its radiotoxicity. Understanding Pu biogeochemical behavior in both near-field (>10-11M) and far-field scales (<10-11M) is imperative to the development of approaches for reprocessing Pu, remediation of Pu contamination and accurate assessment of risks posed by disposal practices for Pu-bearing wastes. The environmental mobility of Pu can be affected by redox potential, pH, adsorption, precipitation, complexation, colloid formation, and microbial activity, of which the first characteristic has the most profound influence. Numerous studies have shown high affinity of Pu towards NOM, as well as to mineral phases. NOM is ubiquitous in the environment, e.g., both fulvic and humic acids are able to reduce Pu(V,VI) to Pu(IV) and the redox potential of NOM is positively related to the abundance of phenolic/acidic OH groups. NOM can either facilitate or limit actinide migration, depending on specific biogeochemical conditions including pH, mineral and organic matter characteristics, etc. The other radionuclide of interest is radioiodine ( 129 I). 129I is a major by-product of nuclear fission and of serious concern to the Department of Energy (DOE) as it is among the top risk drivers at existing and potential radiowaste-contaminated sites. The risk of 129 I stems largely from its high bioconcentration factor (90% of the body’s iodine is accumulated in the thyroid), a high inventory at source terms, a very long-half life (16M years), and rapid mobility in the subsurface environment. As a consequence, 129 I has the lowest drinking water standard (1 pCi/L) among all radionuclides in the Federal Register. With a novel and sensitive gas chromatography-mass spectrometry (GC-MS) method developed in our lab, it is possible to quickly and simultaneously determine the distribution of 129 I and stable 127 I forms in environments, as low as 2 pCi/L for 129 I. This method was subsequently validated using accelerator mass spectroscopy, AMS. IO 3 - and organo-I were determined as major species in the groundwater of SRS and the Hanford Site, contrary to thermodynamic predictions that I- should be the dominant species at these sites. Mobility of 129 I was also demonstrated to depend greatly on the I species and its concentration, sediment pH, and redox state, with times to achieve equilibrium taking up to 12 weeks. Along the groundwater pathway in the F-Area of SRS, 129 I- supplied from the seepage basins was transformed to 129 IO 3 - and organo- 129 I with increasing iodine sediment sorption, causing the lower total 127 I and 129 I concentrations along the gradient transect of the waste plume. By contrast, groundwater 129 I concentrations in the wetlands (as high as 1617.3 pCi/L) were greatly elevated with respect to the source term (159.3 pCi/L). While the NOM promoted the uptake of 129 I to the wetland sediment, it also promoted the formation of soluble organic fraction. A small fraction of NOM that is bound to iodine can behave as a mobile organo-I source. Iodide was enzymatically incorporated into NOM, whereas both iodide and iodate were abiotically bound to NOM, under certain conditions. Iodate removal from the mobile aqueous phase can also occur through incorporation into carbonate (e.g., at the Hanford Site, USA). Thus immobilization and re-mobilization of iodine species were influenced by pH, Eh and the presence of NOM and metal oxides, which adds to the complexity of site remediation action. A ground-breaking result was to elucidate the products (i.e. organo-iodine moieties formed via enzymatic and non-enzymatic processes) at the molecular level by nuclear magnetic resonance (NMR) and electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FTICRMS). We found that iodine-NOM interactions may be influenced by NOM hydrophobic aliphatic moieties. From the perspective of ESI-FTICRMS, organo-iodine formulas were ascribed to the groups of unsaturated hydrocarbons, lignins and proteins. Iodate is likely abiotically reduced to reactive iodine species by lignin- and tannin-like compounds or carboxylic-rich alicyclic molecules (CRAM). We also investigated microbial mechanisms in iodine incorporation into NOM. We established that soil bacteria isolated from F-Area of SRS did not accumulate significant amounts of I- (0.2-2%). Intracellular uptake of I- decreases with increasing pH when pH ranged from 4 to 6. In contrast, 44 out of 84 strains isolated from the F-Area of SRS can transform I- to IO 3 - and organo-iodine. In some cases, oxidation was facilitated in the presence of H 2 O 2 . Microbes can also excrete organic acids that enhance I- oxidation by lowering the ambient pH and reacting with H 2 O 2 to form peroxy carboxylic acids. At lower pH values (≤5), H 2 O 2 hydrolysis was the driving force for iodide-oxidation; whereas, at pH ≥ 6, spontaneous decomposition of peroxy carboxylic acids, originating from H 2 O 2 and organic acids were the primary cause of iodide oxidation. Lastly, it was determined that microbial processes involved in Mn (II) are capable of directly oxidizing I- via enzymatic catalysis (i.e., multicopper oxidases), or indirectly through the formation of reactive oxygen species (ROS) and/or biogenic manganese oxides. ROS-mediated oxidation of I- was found to predominate at pH >5, whereas the enzymatic and Mn oxide pathways were more active at pH < 5. Together, this project has resulted in 9 publications in high-impact journals, and the training of 1 Ph.D and 4 undergraduate students.

54 ENVIRONMENTAL SCIENCES↗

Spectral Properties and Coding Transitions of Haar-Random Quantum Codes

A quantum error-correcting code with a nonzero error threshold undergoes a mixed-state phase transition when the error rate reaches that threshold. We explore this phase transition for Haar-random quantum codes, in which the logical information is encoded in a random subspace of the physical Hilbert space. We focus on the spectrum of the encoded system density matrix as a function of the rate of uncorrelated, single-qudit errors. For low error rates, this spectrum consists of well-separated bands, representing errors of different weights. As the error rate increases, the bands for high-weight errors merge. The evolution of these bands with increasing error rate is well described by a simple analytic ansatz. Using this ansatz, as well as an explicit calculation, we show that the threshold for Haar-random quantum codes saturates the hashing bound, and thus coincides with that for random stabilizer codes. For error rates that exceed the hashing bound, typical errors are uncorrectable, but postselected error correction remains possible until a much higher detection threshold. Postselection can in principle be implemented by projecting onto subspaces corresponding to low-weight errors, which remain correctable past the hashing bound.

decoherence↗

EFT approach to the endpoint of muon decay-in-orbit

As upcoming experiments aim to probe muon conversion with unprecedented precision, equally precise theoretical predictions are crucial to maximize discovery potential. This applies not only to the new physics signal, muon-electron conversion, but also to its only irreducible background, muon decay-in-orbit (DIO) near the endpoint. Accurate computation of higher-order corrections in bound states is a long-standing challenge due to the difficulty of systematically organizing contributions. In previous work, we developed an Effective Field Theory framework to address this issue and applied it to muon conversion. Here, we extend this approach to the DIO endpoint, a more complex problem due to the presence of a neutrino-antineutrino pair in the final state. We present the most precise prediction to date of the background spectrum relevant for future muon conversion searches, achieving next-to-leading logarithmic prime accuracy for QED corrections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Effect of Glacial/Interglacial Recharge Conditions on Flow of Meteoric Water Through Deep Orogenic Faults: Insights Into the Geothermal System at Grimsel Pass, Switzerland

Many meteoric-recharged, fault-hosted geothermal systems in amagmatic orogenic belts have been active through the Pleistocene glacial/interglacial climate fluctuations. The effects of such climate-induced recharge variations on fluid flow patterns and residence times of the thermal waters are complex and may influence how the geothermal and mineralization potential of the systems are evaluated. We report systematic thermal–hydraulic simulations designed to reveal the effects of recharge variations, using a model patterned on the orogenic geothermal system at Grimsel Pass in the Swiss Alps. Fault-bound circulation of meteoric water through the Grimsel fault is driven to depths of ~10 km by the high alpine topography. Simulations suggest that the current single pass flow is typical of interglacial periods, during which 1) meteoric recharge into the fault is high (above tens of centimeters per year), 2) conditions are at or somewhat below the critical Rayleigh number, and 3) the hydraulic connectivity along the fault plane is extensive (an extent of at least 10 km into increasingly higher terrain is required to explain the 10 km penetration depth). The subcritical condition constrains the bulk fault permeability to < 1e-14 m2. In contrast, the limited recharge during the numerous Pleistocene glaciation events likely induced a layered flow system with single pass flow confined to shallow depths while non-Rayleigh convection occurred in the deep fault. The same layering can be observed at low aspect ratios (length/depth) of the fault plane, when the available recharge area limits the flux through the fault.

58 GEOSCIENCES↗

Iron transformation mediates phosphate retention across a permafrost thaw gradient

Phosphorus limits primary productivity in many (Sub-)Arctic ecosystems and may constrain biological carbon sequestration. Iron (III) oxides strongly bind phosphate in soils but can dissolve under flooded, reducing conditions induced by permafrost thaw and ground collapse. The ability for iron to regulate phosphate storage and solubility in thawing permafrost landscapes remains unclear. Here, iron-rich sediments containing iron oxides and organic-bound iron were incubated with or without added phosphate in soils along a permafrost thaw gradient to evaluate how iron-phosphate associations respond to thaw-induced redox shifts. Iron oxides partially dissolved and released sorbed phosphate when incubated in soils underlain by degraded permafrost. Iron complexed by organic matter remained stable but provided no phosphate binding capacity. Phosphate addition enhanced iron oxide dissolution and phosphorus concentrations in associated microbial biomass. Our study demonstrates that the capacity for iron oxides to immobilize and retain phosphate in permafrost peatlands decreases with permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗

Sequential Dosing Strategies for Controlling Selectivity and Plasma-Phase Contributions in Plasma Catalysis

Plasma-assisted catalysis has advanced in recent years, particularly for transforming stable reactants at atmospheric pressure and ambient temperature. However, achieving a deeper understanding of the many plasma and catalytic contributions remains a significant goal, as improving product yield and selectivity in plasma catalysis depends on proper catalyst selection, which is often challenging due to the complex interplay between plasma-phase and plasma-surface reactions. A sequential methodology has emerged as a means to decouple the catalyst activity from plasma-phase reactions. In this approach, nonthermal plasma is used in one step to activate and/or convert a gas phase or surface bound reactant, while in a second step, the catalyst directs product formation under steady-state or temperature-programmed conditions. This review examines studies using this technique for reactions involving N 2 , CO 2 , and SO 2 , offering insights into reaction mechanisms and catalyst behavior/selection for these transformations. These systematic studies provide a framework that can be applied to other plasma-assisted reactions. We also highlight remaining questions, propose directions for future studies, and discuss the potential of applying this methodology to other reaction systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing CO 2 dissociation pathways at vicinal copper (997) interfaces

Size- and shape-tailored copper (Cu) nanocrystals can offer vicinal planes for facile carbon dioxide (CO 2 ) activation. Despite extensive reactivity benchmarks, a correlation between CO 2 conversion and morphology structure has not yet been established at vicinal Cu interfaces. Herein, ambient pressure scanning tunneling microscopy reveals step-broken Cu nanocluster evolutions on the Cu(997) surface under 1 mbar CO 2 (g). The CO 2 dissociation reaction produces carbon monoxide (CO) adsorbate and atomic oxygen (O) at Cu step-edges, inducing complicated restructuring of the Cu atoms to compensate for increased surface chemical potential energy at ambient pressure. The CO molecules bound at under-coordinated Cu atoms contribute to the reversible Cu clustering with the pressure gap effect, whereas the dissociated oxygen leads to irreversible Cu faceting geometries. Synchrotron-based ambient pressure X-ray photoelectron spectroscopy identifies the chemical binding energy changes in CO-Cu complexes, which proves the characterized real-space evidence for the step-broken Cu nanoclusters under CO(g) environments. Our in situ surface observations provide a more realistic insight into Cu nanocatalyst designs for efficient CO 2 conversion to renewable energy sources during C 1 chemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An energetics assessment of benzo[ a ]tetracene and benzo[ a ]pyrene as triplet–triplet annihilation emitters

Optical upconversion (UC) of low energy photons into high energy photons enables solar cells to harvest photons with energies below the band gap of the absorber, reducing the transmission loss. UC based on triplet–triplet annihilation (TTA) in organic chromophores can upconvert photons from sunlight, albeit with low conversion efficiency. We utilize three energy-based criteria to assess the UC potential of TTA emitters in terms of the quantum yield (QY) and the anti-Stokes shift. The energy loss in the singlet pathway of an emitter encounter complex, where a high energy photon is emitted, determines whether a chromophore may undergo TTA. The energy loss in the triplet pathway, which is the main competing process, impacts the TTA QY. The energy difference between the lowest singlet and triplet excitation states in TTA emitters sets an upper bound for the anti-Stokes shift of TTA-UC. Using the energetic criteria evaluated by time-dependent density functional theory (TDDFT) calculations, we find that benzo[a]tetracene, benzo[a]pyrene, and their derivatives are promising TTA emitters. The energetics assessment and computer simulations could be used to efficiently discover and design more candidate high-performance TTA emitters.

36 MATERIALS SCIENCE↗

Crystal structure of an Escherichia coli Hfq Core (residues 2–69)–DNA complex reveals multifunctional nucleic acid binding sites

Hfq regulates bacterial gene expression post-transcriptionally by binding small RNAs and their target mRNAs, facilitating sRNA-mRNA annealing, typically resulting in translation inhibition and RNA turnover. Hfq is also found in the nucleoid and binds double-stranded (ds) DNA with a slight preference for A-tracts. Here, we present the crystal structure of the Escherichia coli Hfq Core bound to a 30 bp DNA, containing three 6 bp A-tracts. Although previously postulated to bind to the ‘distal’ face, three statistically disordered double stranded DNA molecules bind across the proximal face of the Hfq hexamer as parallel, straight rods with B-DNA like conformational properties. One DNA duplex spans the diameter of the hexamer and passes over the uridine-binding proximal-face pore, whereas the remaining DNA duplexes interact with the rims and serve as bridges between adjacent hexamers. Binding is sequence-independent with residues N13, R16, R17 and Q41 interacting exclusively with the DNA backbone. Atomic force microscopy data support the sequence-independent nature of the Hfq-DNA interaction and a role for Hfq in DNA compaction and nucleoid architecture. Our structure and nucleic acid-binding studies also provide insight into the mechanism of sequence-independent binding of Hfq to dsRNA stems, a function that is critical for proper riboregulation.

59 BASIC BIOLOGICAL SCIENCES↗

Peer-to-Peer Communication Trade-Offs for Smart Grid Applications: Preprint

Peer-to-peer energy management systems for smart grids require developers to consider the trade-offs between the amount of communication traffic generated and the quality and speed of convergence of the control algorithms that are deployed. Employing a fully connected communication causes messages to scale exponentially with the number of nodes, while using a sparse connectivity causes less information dissemination leading to degradation of the algorithm performance. The best communication topology for a particular application lies somewhere in between and often requires empirical evaluation by application designers. Existing methods do not put focus on the needs for smart grid applications, which is information dissemination throughout the network and they do not provide a flexible solution for application developers to prototype and deploy different topologies without modifying the application code. This paper introduces a configurable virtual communication topology framework TopLinkMgr, allowing users to specify any chosen communication topology and deploy peer-to-peer applications using it. It also introduces a self-adaptive, fault-tolerant topology management algorithm, Bounded Path Dissemination that can ensure the dissemination of information to all peers within a specified threshold for a sparsely connected topology. Experiments show that the algorithm improves on convergence speed and accuracy over state-of-the-art methods and is also robust against node failures. The results indicate the possibility of achieving a close-to optimal convergence without overloading the network allowing the realization of peer-to-peer control platforms covering larger and more complex power systems.

Bounded Path Dissemination↗