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Privacy-Assured Aggregation Protocol for Smart Metering: A Proactive Fault-Tolerant Approach [Proactive Fault-Tolerant Aggregation Protocol for Privacy-Assured Smart Metering]
Smart meters are integral to demand response in emerging smart grids, by reporting the electricity consumption of users to serve application needs. But reporting real-time usage information for individual households raises privacy concerns. Existing techniques to guarantee differential privacy (DP) of smart meter users either are not fault tolerant or achieve (possibly partial) fault tolerance at high communication overheads. In this paper, we propose a fault-tolerant protocol for smart metering that can handle general communication failures while ensuring DP with significantly improved efficiency and lower errors compared with the state of the art. Our protocol handles fail-stop faults proactively by using a novel design of future ciphertexts, and distributes trust among the smart meters by sharing secret keys among them. We prove the DP properties of our protocol and analyze its advantages in fault tolerance, accuracy, and communication efficiency relative to competing techniques. We illustrate our analysis by simulations driven by real-world traces of electricity consumption.
Primary Frequency Response with Aggregated DERs
Power networks have to withstand a variety of disturbances that affect system frequency, and the problem is compounded with the increasing integration of intermittent renewable generation. Following a large-signal generation or load disturbance, system frequency is arrested leveraging primary frequency control provided by governor action in synchronous generators. In this work, we propose a framework for distributed energy resources (DERs) deployed in distribution networks to provide (supplemental) primary frequency response. Particularly, we demonstrate how power-frequency droop slopes for individual DERs can be designed so that the distribution feeder presents a guaranteed frequency-regulation characteristic at the feeder head. Furthermore, the droop slopes are engineered such that injections of individual DERs conform to a well-defined fairness objective that does not penalize them for their location on the distribution feeder. Time-domain simulations for an illustrative network composed of a combined transmission network and distribution network with frequency-responsive DERs are provided to validate the approach.
How Snow Aggregate Ellipsoid Shape and Orientation Variability Affects Fall Speed and Self-Aggregation Rates
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The Ice Particle and Aggregate Simulator (IPAS). Part II: Analysis of a Database of Theoretical Aggregates for Microphysical Parameterization
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Flow Partitioning in Fully Saturated Soil Aggregates
Microbes play an important role in facilitating organic matter decomposition in soils, which is a major component of the global carbon cycle. Microbial dynamics are intimately coupled to environmental transport processes, which control access to labile organic matter and other nutrients that are needed for the growth and maintenance of microorganisms. Transport of soluble nutrients in the soil system is arguably most strongly impacted by preferential flow pathways in the soil. Since the physical structure of soils can be characterized as being formed from constituent micro aggregates which contain internal porosity, one pressing question is the partitioning of the flow among the “inter-aggregate” and “intra-aggregate” pores and how this may impact overall solute transport within heterogeneous soil structures. The answer to this question is particularly important in evaluating assumptions to be used in developing upscaled simulations based on highly-resolved mechanistic models. We constructed a number of diverse multi-aggregate structures with different packing ratios by stacking micro-aggregates containing internal pores and varying the size and shape of inter-aggregate pore spacing between them. We then performed pore-scale flow simulations using computational fluid dynamics methods to determine the flow patterns in these aggregate-of-aggregates structures and computed the partitioning of the flow through intra- and inter-aggregate pores as a function of the spacing between the aggregates. The results of these numerical experiments demonstrate that soluble nutrients are largely transported via flows through inter-aggregate pores. Although this result is consistent with intuition, we have also been able to quantify the relative flow capacity of the two domains under various conditions. For example, in our simulations, the flow capacity through the aggregates (intra-aggregate flow) was less than 2% of the total flow when the spacing between the aggregates was larger than 18 micron. Inter-aggregate pores continued to be the dominant flow pathways even at much smaller spacing; intra-aggregate flow was less than 10% of the total flow when the inter- and intra-aggregate pore sizes were comparable. Such studies are making it possible to identify which model upscaling assumptions are realistic and what computational methods are required for detailed numerical investigation of microbial carbon cycling dynamics in soil systems.
Exciton Delocalization in Indolenine Squaraine Aggregates Templated by DNA Holliday Junction Scaffolds
Exciton delocalization plays a prominent role in the photophysics of molecular aggregates, ultimately governing their particular function or application. DNA is a compelling scaffold in which to template molecular aggregates and promote exciton delocalization. As individual dye molecules are the basis of exciton delocalization in molecular aggregates, their judicious selection is important. Motivated by their excellent photostability and spectral properties, here we examine the ability of squaraine dyes to undergo exciton delocalization when aggregated via a DNA Holliday junction (HJ) template. A commercially available indolenine squaraine dye was chosen for the study given its strong structural resemblance to Cy5, a commercially available cyanine dye previously shown to undergo exciton delocalization in DNA HJs. Three types of DNA-dye aggregate configurations—transverse dimer, adjacent dimer, and tetramer—were investigated. Signatures of exciton delocalization were observed in all squaraine-DNA aggregates. Specifically, strong blue shift and Davydov splitting were observed in steady-state absorption spectroscopy and exciton-induced features were evident in circular dichroism spectroscopy. Strongly suppressed fluorescence emission provided additional, indirect evidence for exciton delocalization in the DNA-templated squaraine dye aggregates. To quantitatively evaluate and directly compare the excitonic Coulombic coupling responsible for exciton delocalization, the strength of excitonic hopping interactions between the dyes were obtained by simultaneous fitting the experimental steady-state absorption and CD spectra via a Holstein-like Hamiltonian in which, following the theoretical approach of Kühn, Renger, and May, the dominant vibrational mode is explicitly considered. The excitonic hopping strength within indolenine squaraines was found to be comparable to that of the analogous Cy5 DNA-templated aggregate. The squaraine aggregates adopted primarily an H-type (dyes oriented parallel to each other) spatial arrangement. Extracted geometric details of dye mutual orientation in the aggregates enabled close comparison of aggregate configurations and the elucidation of the influence of dye angular relationship on excitonic hopping interactions in squaraine aggregates. Furthermore, these results encourage the application of squaraine-based aggregates in next generation systems driven by molecular excitons.
Spatial and Temporal Uncertainty of Crop Yield Aggregations
The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.
Cytoprotective role of ubiquitin against toxicity induced by polyglutamine-expanded aggregates
Highlights: • Formation of IBs composed of Q103 aggregates is independent of cellular Ub levels. • Ub deficiency is sufficient to cause the accumulation of Q103 aggregates in MEFs. • Ub deficiency leads to impaired autophagic clearance of Q103 aggregates in MEFs. • Ub-deficient MEFs are more susceptible to the toxicity caused by Q103 aggregates. Ubiquitin (Ub) homeostasis is important for cellular function and survival, especially under stress conditions. Recently, we have demonstrated that Ubc{sup −/−} (Ub-deficient) mouse embryonic fibroblasts (MEFs) exhibited reduced viability under oxidative stress induced by arsenite, which was not due to dysregulation of the antioxidant response pathway, but rather due to the potential toxicity caused by the misfolded protein aggregates. However, it is still not clear whether Ub deficiency is directly related to the accumulation of toxic protein aggregates, as arsenite itself triggers protein aggregation and renders cells into aberrant conditions such as reduced proteasome function and inhibition of autophagic flux. Therefore, under arsenite treatment, the outcome could be derived from the combination of multiple defective pathways. Furthermore, it has also been suggested that ubiquitination status of misfolded proteins may not be important for the formation of inclusion bodies composed of misfolded protein aggregates. We therefore wondered whether Ub deficiency is sufficient to trigger the accumulation of toxic protein aggregates inside the cells. In this study, we ectopically expressed polyQ-expanded aggregates (Q103) in MEFs and observed inclusion body formation at the juxtanuclear region, which was independent of cellular Ub levels. In contrast to arsenite treatment, polyQ expression did not affect proteasome function. However, we observed an increased accumulation of Q103 aggregates in Ubc{sup −/−} MEFs, which was due to impaired autophagic clearance. Finally, we demonstrated that the increased accumulation of Q103 aggregates under Ub deficiency dramatically reduced the viability of cells. Therefore, our results suggest that the maintenance of proper levels of cellular Ub is important to protect cells against the toxicity induced by the accumulation of protein aggregates.
Subtle Molecular Changes Largely Modulate Chiral Helical Assemblies of Achiral Conjugated Polymers by Tuning Solution-State Aggregation
Understanding the solution-state aggregate structure and the consequent hierarchical assembly of conjugated polymers is crucial for controlling multiscale morphologies during solid thin-film deposition and the resultant electronic properties. However, it remains challenging to comprehend detailed solution aggregate structures of conjugated polymers, let alone their chiral assembly due to the complex aggregation behavior. Herein, we present solution-state aggregate structures and their impact on hierarchical chiral helical assembly using an achiral diketopyrrolopyrrole-quaterthiophene (DPP-T4) copolymer and its two close structural analogues wherein the bithiophene is functionalized with methyl groups (DPP-T2M2) or fluorine atoms (DPP-T2F2). Combining in-depth small-angle X-ray scattering analysis with various microscopic solution imaging techniques, we find distinct aggregate in each DPP solution: (i) semicrystalline 1D fiber aggregates of DPP-T2F2 with a strongly bound internal structure, (ii) semicrystalline 1D fiber aggregates of DPP-T2M2 with a weakly bound internal structure, and (iii) highly crystalline 2D sheet aggregates of DPP-T4. These nanoscopic aggregates develop into lyotropic chiral helical liquid crystal (LC) mesophases at high solution concentrations. Intriguingly, the dimensionality of solution aggregates largely modulates hierarchical chiral helical pitches across nanoscopic to micrometer scales, with the more rigid 2D sheet aggregate of DPP-T4 creating much larger pitch length than the more flexible 1D fiber aggregates. Combining relatively small helical pitch with long-range order, the striped twist-bent mesophase of DPP-T2F2 composed of highly ordered, more rigid 1D fiber aggregate exhibits an anisotropic dissymmetry factor (g-factor) as high as 0.09. This study can be a prominent addition to our knowledge on a solution-state hierarchical assembly of conjugated polymers and, in particular, chiral helical assembly of achiral organic semiconductors that can catalyze an emerging field of chiral (opto)electronics.
The Shape and Density Evolution of Snow Aggregates
Abstract Snow aggregates evolve into a variety of observed shapes and densities. Despite this diversity, models and observational studies employ fractal or Euclidean geometric measures that are assumed universal for all aggregates. This work therefore seeks to improve understanding and representation of snow aggregate geometry and its evolution by characterizing distributions of both observed and Monte Carlo–generated aggregates. Two separate datasets of best-fit ellipsoid estimates derived from Multi-Angle Snowflake Camera (MASC) observations suggest the use of a bivariate beta distribution model for capturing aggregate shapes. Product moments of this model capture shape effects to within 4% of observations. This mathematical model is used along with Monte Carlo simulated aggregates to study how combinations of monomer properties affect aggregate shape evolution. Plate aggregates of any aspect ratio produce a consistent ellipsoid shape evolution whereas thin column aggregates evolve to become more spherical. Thin column aggregates yield fractal dimensions much less than the often-assumed value of 2.0. Ellipsoid densities and fractal analogs of density (lacunarity) are much more variable depending on combinations of monomer size and shape. Simple mathematical scaling relationships can explain the persistent triaxial ellipsoid shapes that appear in both observed and modeled aggregates. Overall, both simulations and observations prove aggregates are rarely oblate. Therefore, the use of the proposed bivariate ellipsoid distribution in models will allow for similar-sized aggregates to exhibit a realistic dispersion of masses and fall speeds.
Spatio-temporal microbial community dynamics within soil aggregates
Soil microbial communities are highly spatially organized, shaped in part by the structure of soil itself. Understanding how spatially discrete microbial communities change across years and seasons in response to environmental factors, plant phenology and aggregate turnover, is key to understanding how varying management practices impact the ecology of soil microbial communities. We investigated both seasonal (within year) and annual (across sampling years) changes of discrete microbial communities in soil aggregate fractions, large macroaggregates (LM) and microaggregates (MICRO) in three different bioenergy management systems. We hypothesized that 1) seasonal changes due to plant phenology and aggregate turnover will be most pronounced within the MICRO aggregate soil microbial community; 2) inter-annual variability will lead to changes in microbial diversity across aggregate sizes and the magnitude of change will be mediated by management regime. We found that LM and MICRO aggregates have unique microbial communities within soil. MICRO aggregate microbial communities are more diverse and change more dynamically across the sampling season, peaking in diversity at peak plant growth and maximum biomass. The number of families indicative of specific MICRO aggregate habitats increases over the growing season for both bacteria (from 3 to 51) and fungi (from 8 to 14). The LM aggregates harbored less diverse, yet more stable, communities within a growing season. By contrast, between years the LM aggregates were the most responsive to inter-annual variability. Our study demonstrates the importance of including the spatio-temporal dynamics of soil microbes. We identified “hot spots” of microbial diversity within soil, with a greater diversity of microbes found under prairies, within the MICRO aggregates, and seasonally during peak plant biomass. Targeted analysis of the MICRO aggregates can contribute to deeper understanding of potential diversity and functioning of soil microbial communities for ecosystem maintenance as well as the response to climatic events and environmental change.
Molecular Mechanisms of Sorbed Ion Effects during Boehmite Particle Aggregation
Classical theories of particle aggregation, such as Derjaguin–Landau–Verwey–Overbeek (DLVO), do not explain recent observations of ion-specific effects or the complex concentration dependence for aggregation. Thus, here, we probe the molecular mechanisms by which selected alkali nitrate ions (Na + , K + , and NO 3 –) influence aggregation of the mineral boehmite (γ-AlOOH) nanoparticles. Nanoparticle aggregation was analyzed using classical molecular dynamics (CMD) simulations coupled with the metadynamics rare event approach for stoichiometric surface terminations of two boehmite crystal faces. Calculated free energy landscapes reveal how electrolyte ions alter aggregation on different crystal faces relative to pure water. Consistent with experimental observations, we find that adding an electrolyte significantly reduces the energy barrier for particle aggregation (~3–4×). However, in this work, we show this is due to the ions disrupting interstitial water networks, and that aggregation between stoichiometric (010) basal–basal surfaces is more favorable than between (001) edge–edge surfaces (~5–6×) due to the higher interfacial water densities on edge surfaces. The interfacial distances in the interlayer between aggregated particles with electrolytes (~5–10 Å) are larger than those in pure water (a few Ångströms). Together, aggregation/disaggregation in salt solutions is predicted to be more reversible due to these lower energy barriers, but there is uncertainty on the magnitudes of the energies that lead to aggregation at the molecular scale. By analyzing the peak water densities of the first monolayer of interstitial water as a proxy for solvent ordering, we find that the extent of solvent ordering likely determines the structures of aggregated states as well as the energy barriers to move between them. Further, the results suggest a path for developing a molecular-level basis to predict the synergies between ions and crystal faces that facilitate aggregation under given solution conditions. Such fundamental understanding could be applied extensively to the aggregation and precipitation utilization in the biological, pharmaceutical, materials design, environmental remediation, and geological regimes.
Simulation of radioactive plume transport in the atmosphere including dynamics of particle aggregation and breakup
Accurate prediction of the atmospheric transport of debris particles relies heavily on our knowledge of the size distribution of the particles within a debris cloud. Assuming a fixed particle size during simulations is not always viable since the size distribution of the debris can change during transport. Various microphysical processes, such as aggregation and breakup, influence debris particles and dictate any changes to the size distribution. To track those changes that can occur, a population balance model can be adopted and instituted within a model framework. Nonetheless, many of the models that simulate the transport of radioactive debris following a device-driven fission incident have historically neglected to consider these processes. As such, this work describes our effort to develop a modeling framework capable of simulating the transport and deposition of a radioactive plume generated from a fission incident with a dynamic population balance including particle aggregation and breakup. Herein the impact of aggregation and breakup, individually and collectively, on the particle size distribution is explored using the developed framework. When simulating aggregation, for example, six mechanisms, including Brownian coagulation, the convective enhancement to Brownian coagulation, van der Waals-viscous force correction for Brownian coagulation, gravitational collection, turbulent inertial motion, and turbulent shear, are considered. Brownian coagulation and its corrections have, as one would expect, a large impact on relatively small aggregates. Aggregates with a diameter that is less than or equal to 1.0 μm, for instance, comprise 50.6 vol % of all aggregates in the absence of aggregation and 31.2 vol % when Brownian coagulation and its corrections are considered. Gravitational collection and, to a much lesser extent, turbulent shear and turbulent inertial motion are, conversely, of great importance to relatively large aggregates (i.e., diameter greater than 3.0 μm). Additionally, the individual effects of atmospheric and particle parameters, such as wind speed and particle density, are examined. Of the parameters examined, turbulent energy dissipation and aggregate fractal dimension (i.e., aggregate shape with lower values representing more irregular particles) were of substantial importance since both terms directly impact aggregate stability and, by extension, the breakup rate. Large-scale transport and deposition simulations in a dry atmosphere are also presented and discussed as a proof of concept.
Relaxation times and modes of disturbed aggregate distribution in micellar solutions with fusion and fission of micelles
We have performed direct numerical calculations of the kinetics of relaxation in the system of surfactant spherical micelles under joint action of the molecular mechanism with capture and emission of individual surfactant molecules by molecular aggregates and the mechanism of fusion and fission of the aggregates. As a basis, we have taken the difference equations of aggregation and fragmentation in the form of the generalized kinetic Smoluchowski equations for aggregate concentrations. The calculations have been made with using the droplet model of molecular surfactant aggregates and two modified Smoluchowski models for the coefficients of aggregate-monomer and aggregate-aggregate fusions which take into account the effects of the aggregate size and presence of hydrophobic spots on the aggregate surface. A full set of relaxation times and corresponding relaxation modes for nonequilibrium aggregate distribution in the aggregation number has been found. The dependencies of these relaxation times and modes on the total concentration of surfactant in the solution and the special parameter controlling the probability of fusion in collisions of micelles with other micelles have been studied.
A model for the kinetics of homotypic cellular aggregation under static conditions
We present the formulation and testing of a mathematical model for the kinetics of homotypic cellular aggregation. The model considers cellular aggregation under no-flow conditions as a two-step process. Individual cells and cell aggregates 1) move on the tissue culture surface and 2) collide with other cells (or aggregates). These collisions lead to the formation of intercellular bonds. The aggregation kinetics are described by a system of coupled, nonlinear ordinary differential equations, and the collision frequency kernel is derived by extending Smoluchowski's colloidal flocculation theory to cell migration and aggregation on a two-dimensional surface. Our results indicate that aggregation rates strongly depend upon the motility of cells and cell aggregates, the frequency of cell-cell collisions, and the strength of intercellular bonds. Model predictions agree well with data from homotypic lymphocyte aggregation experiments using Jurkat cells activated by 33B6, an antibody to the beta 1 integrin. Since cell migration speeds and all the other model parameters can be independently measured, the aggregation model provides a quantitative methodology by which we can accurately evaluate the adhesivity and aggregation behavior of cells.
Directed Energy Transfer through DNA-templated J-aggregates
Strongly coupled molecular dye aggregates have unique optoelectronic properties that often resemble those of light harvesting complexes found in nature. The exciton dynamics in coupled dye aggregates could enhance the long-range transfer of optical excitation energy with high efficiency. In principle, dye aggregates could serve as important components in molecular-scale photonic devices, however, rational design of these coupled dye aggregates with precise control over their organization, interactions and dynamics remains a challenge. DNA nanotechnology has recently been used to build an excitonic circuit by organizing pseudoisocyanine (PIC) dyes forming J-aggregates on the templates of poly(dA)-poly(dT) DNA duplexes. Here, the excitonic properties of the PIC J-aggregates on DNA are characterized spectroscopically in detail using poly(dA)-poly(dT) tract lengths of 24 and 48 base pairs. The excitonic properties of these DNA templated dye assemblies depend on the length and sequence of the DNA template. The incorporation of a gap of two GC base pairs between two segments of poly(dA)-poly(dT) DNA markedly reduces the delocalization of excitation in the J-aggregates.Using a quantum dot (QD) as the light absorber and energy donor and using Alexa Fluor 647 (AF647) as the energy acceptor, with a DNA-templated J-aggregate in between, significant energy transfer from QD to AF647 is observed over a distance far longer than possible without the aggregate bridge. By comparing the efficiency of energy transfer through a continuous J-aggregate with the efficiency when the aggregate has a discontinuity in the middle, the effects of energy transfer within the aggregate bridge between the donor and acceptor are evaluated.