Long-range Distributions Research Articles

A simple and intuitive model for long-range 3D potential distributions of in-operando TEM-samples: Comparison with electron holographic tomography

Electron holography is a powerful tool to investigate the properties of micro- and nanostructured electronic devices. A meaningful interpretation of the holographic data, however, requires an understanding of the 3D potential distribution inside and outside the sample. Standard approaches to resolve these potential distributions involve projective tilt series and their tomographic reconstruction, in addition to extensive simulations. Here, a simple and intuitive model for the approximation of such long-range potential distributions surrounding a nanostructured coplanar capacitor is presented. The model uses only independent convolutions of an initial potential distribution with a Gaussian kernel, allowing the reconstruction of the entire potential distribution from only one measured projection. By this, a significant reduction of the required computational power as well as a drastically simplified measurement process is achieved, paving the way towards quantitative electron holographic investigation of electrically biased nanostructures.

Quest for Multifunctionality: Current Progress in the Characterization of Heterometallic Metal-Organic Frameworks.

Metal-organic frameworks (MOFs) are a class of porous, crystalline materials that have been systematically developed for a broad range of applications. Incorporation of two or more metals into a single crystalline phase to generate heterometallic MOFs has been shown to lead to synergistic effects, in which the whole is oftentimes greater than the sum of its parts. Because geometric proximity is typically required for metals to function cooperatively, deciphering and controlling metal distributions in heterometallic MOFs is crucial to establish structure-function relationships. However, determination of short- and long-range metal distributions is nontrivial and requires the use of specialized characterization techniques. Advancements in the characterization of metal distributions and interactions at these length scales is key to rapid advancement and rational design of functional heterometallic MOFs. This perspective summarizes the state-of-the-art in the characterization of heterometallic MOFs, with a focus on techniques that allow metal distributions to be better understood. Using complementary analyses, in conjunction with computational methods, is critical as this field moves toward increasingly complex, multifunctional systems.

Demonstration of Optical Clock-Free Localization and Navigation (CLAN)

Positioning, navigation, and timing (PNT) applications often rely on establishing synchronized clocks to achieve accurate localizations. The accuracy of the measurement is compromised due to clock drifts or inaccurate timing. In this manuscript, we propose and demonstrate autonomous optical clock-free localization and navigation (CLAN) system that eliminates the need for synchronized clocks and uses free-running lasers at the transmitter and receiver sites. Experimentally we show that a remote static or dynamic receiver >1.8km away from the transmitter determines its relative location to the transmitter with a <1cm uncertainty and successfully identifies >2cm incremental changes in distance without using time information. The experimental results are also verified by theoretical modeling and numerical simulations. The proposed technology is proven to be suitable for long-range localizations, autonomous navigations, and timing distributions in GPS-denied environments.

Titin UN2A Acts as a Stable, Non-Polymorphic Scaffold in its Binding to CARP.

The N2A segment of titin functions as a pivotal hub for signal transduction and interacts with various proteins involved in structural support, chaperone activities, and transcriptional regulation. Notably, the "unique N2A" (UN2A) subdomain has been shown to interact with the stress-regulated cardiac ankyrin repeat protein (CARP), which contributes to the regulation of sarcomeric stiffness. Previously, the UN2A domain's three-dimensional structure was modelled based on its secondary structure content identified by NMR spectroscopy, considering the domain in isolation. In this study, we report experimental long-range distance distributions by electron paramagnetic resonance (EPR) spectroscopy between the three helixes within the UN2A domain linked to the immunoglobulin domain I81 in the presence and absence of CARP. The data confirm the central three-helix bundle fold of UN2A and show that this adopts a compact and stable conformation in absence of CARP. After binding to CARP, no significant conformational change was observed, suggesting that the UN2A domain retains its structure upon binding to CARP thereby, mediating the interaction approximately as a rigid-body.

Effect of the pion field on the distributions of pressure and shear in the proton

In light of recent experimental progress in determining the pressure and shear distributions in the proton, these quantities are calculated in a model with confined quarks supplemented by the pion field required by chiral symmetry. The incorporation of the pion contributions is shown to account for the long-range distributions, in general agreement with the experimentally extracted quark contributions. The results of the model are also compared with lattice QCD results at unphysically large quark mass.

Dispersive Broadening of Two-photon Wave Packets Generated via Type-I and Type-II Spontaneous Parametric Down-conversion

Photons generated via spontaneous parametric down-conversion (SPDC) have broad spectrums and suffer from dispersive broadening of the temporal wave packets when they are transmitted through dispersive media. In this paper we theoretically and experimentally study the detailed amount of the temporal broadening of the two-photon wave packets generated via both type-I and type-II SPDC with β-BaB2O4 of various lengths, by transmitting them through optical fibers. We interpret the results with respect to the spectral properties of the two-photon wave packets. We believe that our results will contribute to implementing protocols involving long-range distributions of photon pairs.

Emergence of encounter networks due to human mobility.

There is a burst of work on human mobility and encounter networks. However, the connection between these two important fields just begun recently. It is clear that both are closely related: Mobility generates encounters, and these encounters might give rise to contagion phenomena or even friendship. We model a set of random walkers that visit locations in space following a strategy akin to Lévy flights. We measure the encounters in space and time and establish a link between walkers after they coincide several times. This generates a temporal network that is characterized by global quantities. We compare this dynamics with real data for two cities: New York City and Tokyo. We use data from the location-based social network Foursquare and obtain the emergent temporal encounter network, for these two cities, that we compare with our model. We found long-range (Lévy-like) distributions for traveled distances and time intervals that characterize the emergent social network due to human mobility. Studying this connection is important for several fields like epidemics, social influence, voting, contagion models, behavioral adoption and diffusion of ideas.

The double-histidine Cu²⁺-binding motif: a highly rigid, site-specific spin probe for electron spin resonance distance measurements.

The development of ESR methods that measure long-range distance distributions has advanced biophysical research. However, the spin labels commonly employed are highly flexible, which leads to ambiguity in relating ESR measurements to protein-backbone structure. Herein we present the double-histidine (dHis) Cu(2+)-binding motif as a rigid spin probe for double electron-electron resonance (DEER) distance measurements. The spin label is assembled in situ from natural amino acid residues and a metal salt, requires no postexpression synthetic modification, and provides distance distributions that are dramatically narrower than those found with the commonly used protein spin label. Simple molecular modeling based on an X-ray crystal structure of an unlabeled protein led to a predicted most probable distance within 0.5 Å of the experimental value. Cu(2+) DEER with the dHis motif shows great promise for the resolution of precise, unambiguous distance constraints that relate directly to protein-backbone structure and flexibility.

Measuring efficiency of international crude oil markets: A multifractality approach

The three major international crude oil markets are treated as complex systems and their multifractal properties are explored. The study covers daily prices of Brent crude, OPEC reference basket and West Texas Intermediate (WTI) crude from January 2, 2003 to January 2, 2014. A multifractal detrended fluctuation analysis (MFDFA) is employed to extract the generalized Hurst exponents in each of the time series. The generalized Hurst exponent is used to measure the degree of multifractality which in turn is used to quantify the efficiency of the three international crude oil markets. To identify whether the source of multifractality is long-range correlations or broad fat-tail distributions, shuffled data and surrogated data corresponding to each of the time series are generated. Shuffled data are obtained by randomizing the order of the price returns data. This will destroy any long-range correlation of the time series. Surrogated data is produced using the Fourier-Detrended Fluctuation Analysis (F-DFA). This is done by randomizing the phases of the price returns data in Fourier space. This will normalize the distribution of the time series. The study found that for the three crude oil markets, there is a strong dependence of the generalized Hurst exponents with respect to the order of fluctuations. This shows that the daily price time series of the markets under study have signs of multifractality. Using the degree of multifractality as a measure of efficiency, the results show that WTI is the most efficient while OPEC is the least efficient market. This implies that OPEC has the highest likelihood to be manipulated among the three markets. This reflects the fact that Brent and WTI is a very competitive market hence, it has a higher level of complexity compared against OPEC, which has a large monopoly power. Comparing with shuffled data and surrogated data, the findings suggest that for all the three crude oil markets, the multifractality is mainly due to long-range correlations.

A Self-Consistent Description of the Conformational Behavior of Chemically Denatured Proteins from NMR and Small Angle Scattering

Characterization of the conformational properties of unfolded proteins is essential for understanding the mechanisms of protein folding and misfolding. This information is also fundamental to determining the relationship between flexibility and function in the highly diverse families of intrinsically disordered proteins. Here we present a self-consistent model of conformational sampling of chemically denatured proteins in agreement with experimental data reporting on long-range distance distributions in unfolded proteins using small-angle x-ray scattering and nuclear magnetic resonance pulse-field gradient-based measurements. We find that standard statistical coil models, selected from folded protein databases with secondary structural elements removed, need to be refined to correct backbone dihedral angle sampling of denatured proteins, although they appear to be appropriate for intrinsically disordered proteins. For denatured proteins, pervasive increases in the sampling of more-extended regions of Ramachandran space {50°<ψ < 180°} throughout the peptide chain are found to be consistent with all experimental data. These observations are in agreement with previous conclusions derived from short-range nuclear magnetic resonance data from residual dipolar couplings, leading the way to a self-consistent description of denatured chains that is in agreement with short- and long-range data measured using both spectroscopic and scattering techniques.

Looking down, around, and up: Mechanistic explanation in psychology

Accounts of mechanistic explanation have emphasized the importance of looking down—decomposing a mechanism into its parts and operations. Using research on visual processing as an exemplar, I illustrate how productive such research has been. But once multiple components of a mechanism have been identified, researchers also need to figure out how it is organized—they must look around and determine how to recompose the mechanism. Although researchers often begin by trying to recompose the mechanism in terms of sequential operations, they frequently find that the components of a mechanism interact in complex ways involving positive and negative feedback and that the organization often exhibits highly interactive local networks linked by a few long-range connections (small-worlds organization) and power law distributions of connections. The mechanisms are themselves active systems that are perturbed by inputs but not set in motion by them. Researchers also need to look up—situate a mechanism in its context, which may be a larger mechanism that modulates its behavior. When looking down is combined with looking around and up, mechanistic research results in an integrated, multi-level perspective.

Opposite effects of interactions and disorder on the switching properties of the spin transition compound [Fe II(L) 2][ClO 4] 2 · C 7H 8

We report on a detailed analysis of the thermal transition hysteresis loop and the relaxation curves of the recently investigated compound [Fe II(L) 2][ClO 4] 2 · C 7H 8 [V. Mishra et al., Inorg. Chem. (2008)]. We developed a variant of a previous kinetic cooperative model, modified for including short-range and long-range Gaussian distributions of energy parameters. The resulting set of coupled master equations was solved numerically for the dynamic and the quasi-static case. We have elucidated the various correlations between the distribution widths and the long-range interaction parameter, which basically have opposite effects. It is shown that presence of a steep hysteresis loop may hide a sizable short-range distribution, while the stretched character of the relaxation curves may also hide the presence of strong interactions. We also show that the coherent analysis of the set of relaxation curves at different temperatures does not allow to disentangle properly all the relevant parameters. We discuss these data with respect to the other photomagnetic experiments, T(LIESST) curve and light-induced thermal hysteresis (LITH) loop, and finally we try to address the question of the real nature of the cooperative relaxation process.

Position-Sensitive Radiation Detector with Flexible Light Guide and Liquid Organic Scintillator to Monitor Distributions of Radioactive Isotopes

Position-sensitive detectors consisting of optical fibers such as scintillating fibers, normal optical plastic fibers, and liquid light guides have been developed as radiation sensors to monitor long-range distributions of radioactive isotopes. Because of losses of optical transmission due to radiation damage in high-level radiation environments, however, both scintillating fibers and normal optical plastic fibers are less applicable to areas of high dose rate. In order to develop a flexible fiber-type radiation sensor with good radiation hardness, we propose to use a liquid light guide, the core of which is replaced by a liquid organic scintillator. A liquid light guide consists of flexible cladding material, and can be easily bent. A liquid organic scintillator can generate a much larger number of photons than the original liquid material, leading to a better detection efficiency than a simple liquid light guide; furthermore, it is not significantly damaged by incident radiation. In preliminary experiments using a fast neutron beam, we confirmed that our prototype system can be operated as a position-sensitive radiation detector. Fundamental characteristics such as spatial resolution, detection efficiency and attenuation length of light propagation were examined with two detectors of 2 m and 10 m length. Optical transmission losses due to radiation damage were examined using 60Co gamma rays; no significant transmission loss was observed up to a dose of 1.5 × 104 Gy.

Mapping protein collapse with single-molecule fluorescence and kinetic synchrotron radiation circular dichroism spectroscopy

We have used the combination of single-molecule Förster resonance energy transfer and kinetic synchrotron radiation circular dichroism experiments to probe the conformational ensemble of the collapsed unfolded state of the small cold shock protein CspTm under near-native conditions. This regime is physiologically most relevant but difficult to access experimentally, because the equilibrium signal in ensemble experiments is dominated by folded molecules. Here, we avoid this problem in two ways. One is the use of single-molecule Förster resonance energy transfer, which allows the separation of folded and unfolded subpopulations at equilibrium and provides information on long-range intramolecular distance distributions. From experiments with donor and acceptor chromophores placed at different positions within the chain, we find that the distance distributions in unfolded CspTm agree surprisingly well with a Gaussian chain not only at high concentrations of denaturant, where the polypeptide chain is expanded, but also at low denaturant concentrations, where the chain is collapsed. The second, complementary approach is synchrotron radiation circular dichroism spectroscopy of collapsed unfolded molecules transiently populated with a microfluidic device that enables rapid mixing. The results indicate a beta-structure content of the collapsed unfolded state of approximately 20% compared with the folded protein. This suggests that collapse can induce secondary structure in an unfolded state without interfering with long-range distance distributions characteristic of a random coil, which were previously found only for highly expanded unfolded proteins.

Close to optimal decentralized routing in long-range contact networks

In order to explain the ability of individuals to find short paths to route messages to an unknown destination, based only on their own local view of a social network (the small world phenomenon), Kleinberg [The small-world phenomenon: an algorithmic perspective, Proc. 32nd ACM Symp. on Theory of Computing, 2000, pp. 163–170] proposed a network model based on a d-dimensional lattice of size n augmented with k long-range directed links per node. Individuals behavior is modeled by a greedy algorithm that, given a source and destination, forwards a message to the neighbor of the current holder, which is the closest to the destination. This algorithm computes paths of expected length Θ ( log 2 n / k ) between any pair of nodes. Other topologies have been proposed later on to improve greedy algorithm performance. But, Aspnes et al. [Fault-tolerant routing in peer-to-peer systems, in: Proc. of ACM 3st Symp. on Princ. of Distr. Comp. (PODC 2002), Vol. 31, 2002, pp. 223–232] shows that for a wide class of long-range link distributions, the expected length of the path computed by this algorithm is always Ω ( log 2 n / ( k 2 log log n ) ) . We design and analyze a new decentralized routing algorithm, in which nodes consult their neighbors near by, before deciding to whom forward the message. Our algorithm uses similar amount of computational resources as Kleinberg's greedy algorithm: it is easy to implement, visits O ( log 2 n / log 2 ( 1 + k ) ) nodes on expectation and requires only Θ ( log 2 n / log ( 1 + k ) ) bits of memory—note that [G.S. Manku, M. Naor, U. Wieder, Know thy neighbor's neighbor: the power of lookahead in randomized P2P networks, in: Proc. of 36th ACM STOC 2004, 2004, to appear], shows that any decentralized algorithm visits at least Ω ( log 2 n / k ) on expectation. Our algorithm computes however a path of expected length O ( log n ( log log n ) 2 / log 2 ( 1 + k ) ) between any pair of nodes. Our algorithm might fit better some human social behaviors (such as web browsing) and may also have successful applications to peer-to-peer networks where the length of the path along which the files are downloaded, is a critical parameter of the network performance.

Self-regulated Complexity in Neural Networks

Recordings of spontaneous activity of in vitro neuronal networks reveal various phenomena on different time scales. These include synchronized firing of neurons, bursting events of firing on both cell and network levels, hierarchies of bursting events, etc. These findings suggest that networks' natural dynamics are self-regulated to facilitate different processes on intervals in orders of magnitude ranging from fractions of seconds to hours. Observing these unique structures of recorded time-series give rise to questions regarding the diversity of the basic elements of the sequences, the information storage capacity of a network and the means of implementing calculations. Due to the complex temporal nature of the recordings, the proper methods of characterizing and quantifying these dynamics are on the time---frequency plane. We thus introduce time-series analysis of neuronal network's synchronized bursting events applying the wavelet packet decomposition based on the Haar mother-wavelet. We utilize algorithms for optimal tiling of the time---frequency plane to signify the local and global variations within the sequence. New quantifying observables of regularity and complexity are identified based on both the homogeneity and diversity of the tiling (Hulata et al., 2004, Physical Review Letters 92: 198181---198104 ). These observables are demonstrated while exploring the regularity---complexity plane to fulfill the accepted criteria (yet lacking an operational definition) of Effective Complexity. The presented question regarding the sequences' capacity of information is addressed through applying our observables on recorded sequences, scrambled sequences, artificial sequences produced with similar long-range statistical distributions and on outputs of neuronal models devised to simulate the unique networks' dynamics.

Plate Residual Stress Effects on Dimensional Accuracy in Thermal Cutting

Dimensional inaccuracies induced by thermal cutting processes have not received sufficient attention in the open literature. A series of recent research initiatives, including this one, have demonstrated that thermal cutting can contribute significantly to dimensional inaccuracies in the form of two major mechanisms:thermally induced part distortions andplate movements as the residual stresses in the original plate are relieved to achieve new equilibrium conditions during cutting. For the former, laser cutting and managing heat sink conditions are effective in minimizing the cutting-induced distortions. For the latter, considerations must be given to the residual stress conditions in the plates to be cut so that a proper cutting sequence and layout plan can be developed to mitigate the plate residual stress effects on part/plate movements during cutting. In this paper, a major research program recently completed under the auspices of the Gulf Coast Regional Maritime Technology Center will be summarized. Some of the major findings are as follows:Although steel mill processes and parameters vary significantly from mill to mill, the important residual stress features that are relevant to cutting accuracy are dominated by only a few mill process parameters.Localized short-range residual stresses are not detrimental to cutting accuracy, even if the short-range residual stress magnitude can be high. Long-range residual stress distributions that achieve equilibrium conditions at a length scale of plate width are most important for cutting sequence planning purposes.As a result, a generalized residual stress distribution (long range) has been established for cutting planning purposes, although the detailed features may vary from mill to mill.Through a detailed series of parametric analyses using advanced modeling techniques, it was found that cutting sequencing is very important in mitigating the plate residual stress effects.It is important and practical to ensure the consistency in steel conditions so that a set of cutting procedures can be developed for mitigating plate residual stress effects on cutting accuracy, rather than trying to eliminate residual stresses in mill plates.

Statistical distributions of oligonucleotide combinations: applications in human chromosomes 21 and 22

Statistical properties of distances between all quintuplets and hexaplets are calculated and long-range distributions are observed for certain quintuplets and hexaplets, common in human chromosomes 21 and 22. The oligonucleotides were ordered according to their power-law exponents and this ordering has separated quintuplets or hexaplets which contain consensus sequences of promoters from other random oligonucleotides. These results are in accordance with earlier observations and theoretical predictions and demonstrate a different aspect of long-range correlations in genomic sequences. Comparison of the statistical properties of quintuplets and hexaplets between the two chromosomes is undertaken and it is shown that statistics are universal in the two chromosomes.

Long- and Short-Range Correlations in Genome Organization

We study the size distribution of coding and non-coding regions in DNA sequences. For most organisms we observe that the size distribution Pc(S) of the coding regions of size S shows short range distribution, whereas the size distribution of the non-coding regions follows a power-law decay Pnc(S) ∼ S−1 − μ, with power exponents indicating clear long-range behavior. We argue, using the Generalized Central Limit Theorem, that the long-range distributions observed in the non-coding are related to the lower level clustering of purines and pyrimidines (1d islands) which follow similar long-range laws. We also address the question of clustering of coding segments in the two complementary strands of DNA. We observe a short-range clustering of coding regions in both strands, expressed by an exponential decay in the clustering size distribution. The decay exponent expresses the degree of short-range correlations and the deviation from random clustering.

Superexchange in insulators and semiconductors: II. The range of the exchange interaction

In this paper we discuss the range of exchange interactions in magnetic semiconductors. It is shown that the range depends strongly on the energy required to excite an electron from the fully occupied valence band to the empty magnetic d orbitals. The range of the exchange interaction and of the spin-density distribution is the same when this excitation energy is large. It is found that kinetic exchange and correlation exchange are the dominant contributions. The usual perturbation theory breaks down when the dp excitation energy becomes of the order of the band width. In this case one has to calculate the exchange interaction in a more rigorous way. This limit is discussed using two-particle Green functions. It is found that these results deviate strongly from the ones obtained using perturbation theory. We derive a path model from an analysis of the effective transfer between two magnetic orbitals. Such a model can explain the long-range exchange interactions reported in the last decades in a large number of magnetic semiconductors and semimagnetic semiconductors. This path model can explain the anisotropy of long-range spin-density distributions found in doped semiconductors.