Power-law weighted networks from local attachments

This letter introduces a mechanism for constructing, through a process of distributed decision-making, substrates for the study of collective dynamics on extended power-law weighted networks with both a desired scaling exponent and a fixed clustering coefficient. The analytical results show that the connectivity distribution converges to the scaling behavior often found in social and engineering systems. To illustrate the approach of the proposed framework we generate network substrates that resemble steady state properties of the empirical citation distributions of (i) publications indexed by the Institute for Scientific Information from 1981 to 1997; (ii) patents granted by the U.S. Patent and Trademark Office from 1975 to 1999; and (iii) opinions written by the Supreme Court and the cases they cite from 1754 to 2002.Comment: 18 pages, 3 figures; Proceedings of the IEEE Conference on Decision and Control and the European Control Conference, Orlando, FL, Dec. 2011; Added references; We modified the model in order to take into account extended power-law distributions which better fit to the citations data sets; Added proofs of theorems; Shorten version; Updated plo

Construction and application of a questionnaire for the social scientific investigation of environmental noise effects

A social psychological questionnair has been developed to study the effects of environmental noise and was applied to 636 people living in 19 different areas of Hamburg. The theoretical foundations and the statistical means employed in its development are described. Four main reactions to noise are isolated statistically, and it is determined that these are moderated by several intervening variables, chief of which are coping capacity for noise, the perceived dangerousness of the noise souce, other daily loads and the individual's liability

Network synchronization of groups

In this paper we study synchronized motions in complex networks in which there are distinct groups of nodes where the dynamical systems on each node within a group are the same but are different for nodes in different groups. Both continuous time and discrete time systems are considered. We initially focus on the case where two groups are present and the network has bipartite topology (i.e., links exist between nodes in different groups but not between nodes in the same group). We also show that group synchronous motions are compatible with more general network topologies, where there are also connections within the groups

Plasma Cytokine and Growth Factor Profiling during Free Flap Transplantation

Ischemia and reperfusion (I/R) is an unavoidable condition during free flap transplantation. Restoration of blood flow is usually associated with a profound inflammatory response. Cytokines and growth factors are the functional proteins which exert their specific influence on injury or repair during the healing period. Plasma concentrations of 18 cytokines and growth factor proteins (IL6, IL8, IP10, TNFα, MCP1, Fractalkine, GRO, bFGF, GMCSF, IFNg, MIP1a, VEGF, sCD40L, IL10, TGFα, IL1β, IL12P40, and TNFβ) have been analyzed with respect to I/R status during microsurgery tissue transplantation in both, artery and vein, from patients by multiplexed immunoassay. Both technical feasibility and biostatistics data analysis approaches were thoroughly assessed. It has been found that, from all investigated proteins, the venous plasma levels of IL6 significantly increased during the ischemia period and mostly sustained their high levels during reperfusion, while venous plasma levels of IL8 showed in general a significant increase in the ischemia period followed by a rapid decrease in the reperfusion period. In conclusion, these findings direct toward an active involvement of tissue-resting leukocytes which may become therapeutic targets for concomitant medication in flap surgery to improve wound healing

COVID Aftermath: The Impact of the Pandemic on Florida\u27s Public School Students

The goal of this White Paper is to provide an overview of the current and future impacts the COVID-19 pandemic (“COVID”) has left on Florida’s public school education system. Additionally, this White Paper review shows how public education institutions are still working to address the loss of instructional time and long-term consequences due to pandemic-related school disruptions

Hints of an axion-like particle mixing in the GeV gamma-ray blazar data?

Axion-Like Particles (ALPs), if exist in nature, are expected to mix with photons in the presence of an external magnetic field. The energy range of photons which undergo strong mixing with ALPs depends on the ALP mass, on its coupling with photons as well as on the external magnetic field and particle density configurations. Recent observations of blazars by the Fermi Gamma-Ray Space Telescope in the 0.1-300 GeV energy range show a break in their spectra in the 1-10 GeV range. We have modeled this spectral feature for the flat-spectrum radio quasar 3C454.3 during its November 2010 outburst, assuming that a significant fraction of the gamma rays convert to ALPs in the large scale jet of this blazar. Using theoretically motivated models for the magnetic field and particle density con figurations in the kiloparsec scale jet, outside the broad-line region, we find an ALP mass m(a) similar to (1 ¿ 3).10(-7) eV and coupling g(a gamma) similar to (1 ¿ 3).10(-10) GeV-1 after performing an illustrative statistical analysis of spectral data in four different epochs of emission. The precise values of m(a) and g(a gamma) depend weakly on the assumed particle density con figuration and are consistent with the current experimental bounds on these quantities. We apply this method and ALP parameters found from fitting 3C454.3 data to another flat-spectrum radio quasar PKS1222+216 (4C+21.35) data up to 400 GeV, as a consistency check, and found good fit. We find that the ALP-photon mixing effect on the GeV spectra may not be washed out for any reasonable estimate of the magnetic field in the intergalactic media

Long-lasting XUV activation of helium nanodroplets for avalanche ionization

We study the dynamics of avalanche ionization of pure helium nanodroplets activated by a weak extreme-ultraviolet (XUV) pulse and driven by an intense near-infrared (NIR) pulse. In addition to a transient enhancement of ignition of a nanoplasma at short delay times $\sim200$~fs, long-term activation of the nanodroplets lasting up to a few nanoseconds is observed. Molecular dynamics simulations suggest that the short-term activation is caused by the injection of seed electrons into the droplets by XUV photoemission. Long-term activation appears due to electrons remaining loosely bound to photoions which form stable `snowball' structures in the droplets. Thus, we show that XUV irradiation can induce long-lasting changes of the strong-field optical properties of nanoparticles, potentially opening new routes to controlling avalanche-ionization phenomena in nanostructures and condensed-phase systems

Exact inference for integrated population modelling

Integrated population modelling is widely used in statistical ecology. It allows data from population time series and independent surveys to be analysed simultaneously. In classical analysis the time‐series likelihood component can be conveniently approximated using Kalman filter methodology. However, the natural way to model systems which have a discrete state space is to use hidden Markov models (HMMs). The proposed method avoids the Kalman filter approximations and Monte Carlo simulations. Subject to possible numerical sensitivity analysis, it is exact, flexible, and allows the use of standard techniques of classical inference. We apply the approach to data on Little owls, where the model is shown to require a one‐dimensional state space, and Northern lapwings, with a two‐dimensional state space. In the former example the method identifies a parameter redundancy which changes the perception of the data needed to estimate immigration in integrated population modelling. The latter example may be analysed using either first‐ or second‐order HMMs, describing numbers of one‐year olds and adults or adults only, respectively. The use of first‐order chains is found to be more efficient, mainly due to the smaller number of one‐year olds than adults in this application. For the lapwing modelling it is necessary to group the states in order to reduce the large dimension of the state space. Results check with Bayesian and Kalman filter analyses, and avenues for future research are identified

Incorporating the effect of weather in construction scheduling and management with sine wave curves: application in the United Kingdom

The impact of (adverse) weather is a common cause of delays, legal claims and economic losses in construction projects. Research has recently been carried out aimed at incorporating the effect of weather in project planning; but these studies have focussed on either a narrow set of weather variables, or a very limited range of construction activities or projects. A method for processing a country’s historical weather data into a set of weather delay maps for some representative standard construction activities is proposed. Namely, sine curves are used to associate daily combinations of weather variables to delay and provide coefficients for expected productivity losses. A complete case study comprising the construction of these maps and the associated sine waves for the UK is presented along with an example of their use in building construction planning. Findings of this study indicate that UK weather extends project durations by an average of 21%. However, using climatological data derived from weather observations when planning could lead to average reductions in project durations of 16%, with proportional reductions in indirect and overhead costs