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There are numerous military, commercial, and scientific applications for mobile wireless networks which are able to self-Organize without recousre to any pre-existing infrastructure. We present the Self Organizing Wireless Adaptive Network protocol, a distributed networking protocol capable of managing such networks.
A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a self-organizing map (SOM). Multiple self-organizing maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experiential knowledge gained from decades of operation. Each SOM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.
Self-organizing macrocyclic receptor-sensors for phosphorus oxyanions, phosphates, and phosphonates comprising imine moieties were prepared by condensation of dipyrrolylmethane dicarbaldehyde with diethylene triamine. The incorporation of flexible ethylene moieties endows the macrocycle with unprecedented flexibility and ability to accommodate numerous phosphorus oxyanions from orthophosphate to large anions such as ATP or phosphonate glyphosate. The anion binding was elucidated by NMR titrations, low-temperature NMR, and NOESY NMR. The incorporation of dansyl fluorophore enables sensing of anions using the fluorescence signal, whereas the changes in fluorescence intensity, width of the fluorescence band, and position of the maxima are analyte-specific and useful in recognition and identification of eleven different P-oxyanions in water. The affinity (K assoc ) for Na + salts was H 2 PO 4 − ≈ Methylphosphonate > H 2 P 2 O 7 2− > Phenylphosphonate- > Glyphosate 2− > AMP 2− > ADP 2− > ATP 2− . Interestingly, phosphonates, including methylphosphonate and glyphosate anions, were also found to display a strong affinity (K assoc ∼10 6 M −1 ) while halides, nitrate, carbonates, or hydrogen sulfate did not show a significant affinity. The determined fluorescence spectral parameters were used to classify the 12 analytes (11 anions and water) using Linear Discriminant Analysis (LDA). Quantification was performed using LDA and Support Vector Machine (SVM), and the phosphonate concentrations in unknown samples were determined with an error of 3.5% or lower.
The primary goals of the project are a) improve the understanding of transport processes, chemical reactions and plasma-driven self-organization such as stratification and filamentation, formation of anode spots, liquid droplets ejection from cathodes, and plasma electrolysis, b) utilize and share among the project participants computational tools developed by the participants to understand plasma-based surface functionalization and plasma-enabled pattern nucleation in a wide range of scales from nano- to millimeters, and c) use experimental methods and facilities available at the University of Alabama in Huntsville (UAH) and Sandia National Laboratories (SNL) to understand and control plasma processes, reaction pathways and the electric nature of self-organization of the plasma-exposed interface structures.
This final report presents the progress made for the DOE-SC0020623 for the period of performance between January 1 2020 and September 30 2024. The research project is entitled "Kinetic effects of self-organization in low-temperature magnetized plasmas", in which kinetic theory and simulations are used to under stand self-organization patterns.
The excess low-frequency 1/f noise and discrete two-level resistance fluctuations (TLFs) were studied in small-area NbN-MgO-NbN tunnel junctions with a high, low-temperature density of active defects. Strong and evolving interactions between large TLFs indicate that these fluctuations result from the self-organization of interacting defect elements. In the low-T tunneling regime, an unusual slowing down of the rates and a decrease in amplitude with increasing T is sometimes observed indicative of a thermally induced change in the self-organized two-level state.
Recent observations of the magnetotail plasma sheet have shown it to be a dynamic and turbulent region. Research has found strong turbulence in the plasma sheet at approximately 20 Earth's Radius tailward of Earth; the turbulence is observed at all activity levels. The existence of strong turbulence in the plasma sheet in the region associated with substorm onset might be thought difficult to reconcile with the coherence and repeatability of the substorm cycle. We review a variety of evidence that strongly suggests the magnetotail is driven, through magnetic flux transfer, into a state of "self-organized criticality" (SOC). It is an important property of physical systems that evolve into SOC that they self-organize into a unique, global dynamic state. This global state is inevitable, and repeatable. In this state, however, small-spatiotemporal-scale system fluctuations are unpredictable and can be only described statistically. This is the basis, we think, for the global coherence and repeatability of the substorm phenomenon in the turbulent plasma sheet. At, or near, substorm onset the plasma sheet can be described by a global SOC state containing significant small scale turbulence. In several recent studies, "sandpile" models were driven into SOC and then shown to reproduce various measures of substorm activity. We discuss the plasma physical foundation of these sandpile models. The evolution of simple continuum plasma sheet models into SOC-like states of many small reconnection events in the turbulent plasma sheet under the will be demonstrated. We view the substorm phenomenon as an avalanche assumption that the plasma sheet is in a SOC state.
Increasing the number of particles in a system often leads to qualitative changes in its properties, such as breaking of symmetries and the appearance of phase transitions. This renders a macroscopic system fundamentally different from its individual microscopic constituents. Lying between these extremes, mesoscopic systems exhibit microscopic fluctuations that influence behaviour on longer length scales, leading to critical phenomena and dynamics. Therefore, tracing the properties of well-controlled mesoscopic systems can help bridge the gap between an exact description of few-body microscopic systems and the emergent description of many-body systems. Here we explore the mesoscopic signatures of an optomechanical self-organization phase transition using arrays of cold atoms inside an optical cavity. By precisely engineering atom–cavity interactions, we reveal how critical behaviour depends on the atom number, identify characteristic dynamical behaviours in the self-organized regime and observe a finite optomechanical susceptibility at the critical point. These findings advance our understanding of particle-number- and time-resolved properties of phase transitions in mesoscopic systems.
Stochastic control optimization, examining self organizing approach for performance adaptive controller with asymptotic optimal properties
Here, irradiation-driven multiphase self-organization presents emergent opportunities for the customization of nanoscale engineering properties, dynamically tuning strain-field distributions and interfacial electronic structures. Responding to intense electronic excitation-induced energy deposition, the dominant phase transformations, with varying Gibbs free energy $Δ,G^o_f$ are confirmed as β → κ → γ → δ that are located in specific microregions for Gallium (III) oxide (Ga 2 O 3 ), as follows: (i) Surface-localized interstitial accumulation under compressive stress triggers β → δ via semi-coherent interface formation. (ii) Tensile stress within latent tracks drives vacancy-mediated oxygen layer truncation (4/12 periodicity along ⟨0001⟩), stabilizing coherent 4H (ABCB) κ and 3C (ABC) β (ABC) interfaces through strain-compensated octahedral distortion. (iii) Screw dislocation-mediated lattice relaxation induces β → γ via cation disordering (Ga 3+ occupancy at β-interstitial sites), forming metastable spinel γ with mixed occupancy across 16d/8a Wyckoff sites. Irradiation-driven β-Ga 2 O 3 →κ/γ/δ transitions, as mechanistically revealed via inelastic thermal spike (i-TS) calculations and molecular dynamics simulations, induce defect-mediated nonlinear photoresponse, critical for optoelectronic engineering.
The main emphasis has been on the programming language for a self organizing computer. An example of programming with the language of finite state machines is presented in a real time processing for weather radars.
A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.
An integrated control and electromagnetic/antenna formulation is presented for evaluating the performance of a distributed antenna system as a function of formation geometry. A distributed and self-organizing control law for the control law for the control of multiple antennas in Low Earth Orbit (LEO) is presented. The control system provides collaborative commanding and performance optimization to configure and operate the distributed formation system. A large aperture antenna is thereby realized by a collection of miniature sparse antennas in formation. A case study consisting of a simulation of four antennas in Low Earth orbit (LEO)is presented to demonstrate the concept.
On the path from inanimate to animate matter, a key step was the self-organization of molecules into protocells - the earliest ancestors of contemporary cells. Studies of the properties of protocells and the mechanisms by which they maintained themselves and reproduced are an important part of astrobiology. These studies also have the potential to greatly impact research in nanotechnology and computer science. Previous studies of protocells have focussed on self-replication. In these systems, Darwinian evolution occurs through a series of small alterations to functional molecules whose identities are stored. Protocells, however, may have been incapable of such storage. We hypothesize that under such conditions, the replication of functions and their interrelationships, rather than the precise identities of the functional molecules, is sufficient for survival and evolution. This process is called non-genomic evolution. Recent breakthroughs in experimental protein chemistry have opened the gates for experimental tests of non-genomic evolution. On the basis of these achievements, we have developed a stochastic model for examining the evolutionary potential of non-genomic systems. In this model, the formation and destruction (hydrolysis) of bonds joining amino acids in proteins occur through catalyzed, albeit possibly inefficient, pathways. Each protein can act as a substrate for polymerization or hydrolysis, or as a catalyst of these chemical reactions. When a protein is hydrolyzed to form two new proteins, or two proteins are joined into a single protein, the catalytic abilities of the product proteins are related to the catalytic abilities of the reactants. We will demonstrate that the catalytic capabilities of such a system can increase. Its evolutionary potential is dependent upon the competition between the formation of bond-forming and bond-cutting catalysts. The degree to which hydrolysis preferentially affects bonds in less efficient, and therefore less well-ordered, peptides is also critical to evolution of a non-genomic system. Based on these results, a new computational object called a "molnet" is defined. Like a neural network, it is formed of interconnected units that send "signals" to each other. Like molecules, neural networks have a specific function once their structure is defined. The difference between a molnet and traditional neural networks, is that input to molnets is not simply passed along and processed from input to output units, but rather it is utilized to form and break connections(bonds), and thus to form new structures. Molnets represent a powerful tool that can be used to understand the conditions under which chemical systems can form large molecules, such as proteins, and display ever more complex functions. This has direct applications, for example to the design of smart,synthetic fabrics. Additional information is contained in the original.
Critical indices beta, gamma delta, nv, etc. are defined and calculated for self-organized critical phenomena. Scaling relations are derived and checked numerically. The order-parameter exponent beta describes the spontaneous current and the relaxation to the criticl point. The power spectrum has 'l/f' behavior with the exponent phi = nv x z, where z is the dynamical critical exponent.
Synthesis and design of on-line self-organizing control of multiple goal, multiple actuator systems
Yockey's (1981) interpretation of information theory relative to concepts of self-organization in the origin of life is criticized on the ground that it assumes that each amino acid residue type in a given sequence is an unaided information carrier throughout evolution. It is argued that more than one amino acid residue can act as a unit information carrier, and that this was the case in prebiotic protein evolution. Forward-extrapolation should be used to study prebiotic evolution, not backward-extrapolation. Transposing the near-random internal order of modern proteins to primitive proteins, as Yockey has done, is an unsupported assumption and disagrees with the results of experimental models of the primordial type. Studies indicate that early primary information carriers in evolution were mixtures of free alpha amino acids which necessarily had the capability of sequencing themselves.
This letter presents experimental results on unlubricated friction, which suggests that stick-slip is described by self-organized criticality (SOC). The data, obtained with a pin-on-disc tribometer examines the variation of the friction force as a function of time-or sliding distance. This is the first time that standard tribological equipment has been used to examine the possibility of SOC. The materials were matching pins and discs of aluminium loaded with 250, 500 and 1000 g masses, and matching M50 steel couples loaded with a 1000 g mass. An analysis of the data shows that the probability distribution of slip sizes follows a power law. We perform a careful analysis of all the properties, beyond the two just mentioned, which are required to imply the presence of SOC. Our data strongly support the existence of SOC for stick-slip in dry sliding friction.