Automatic measurement of network parameters : a survey /

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Investigation of swelling and network parameters of poly (ethylene glycol)-crosslinked poly (methyl vinyl ether-co-maleic acid) hydrogels

he influence of poly(ethylene glycol) (PEG) plasticiser content and molecular weight on the physicochemical properties of films cast from aqueous blends of poly(methyl vinyl ether-co-maleic acid) was investigated using thermal analysis, swelling studies, scanning electron microscopy (SEM) and attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy. FTIR spectroscopy revealed a shift of the CO peak from 1708 to 1731 cm-1, indicating that an esterification reaction had occurred upon heating, thus producing crosslinked films. Higher molecular weight PEGs (10,000 and 1000 Da, respectively), having greater chain length, producing hydrogel networks with lower crosslink densities and higher average molecular weight between two consecutive crosslinks. Accordingly, such materials exhibited higher swelling rates. Hydrogels crosslinked with a low molecular weight PEG (PEG 200) showed rigid networks with high crosslink densities and, therefore, lower swelling rates. Polymer:plasticizer ratio alteration did not yield any discernable patterns, regardless of the method of analysis. The polymer–water interaction parameter (?) increased with increases in the crosslink density. SEM studies showed that porosity of the crosslinked films increased with increasing PEG MW, confirming what had been observed with swelling studies and thermal analysis, that the crosslink density must be decreased as the Mw of the crosslinker is increased. Hydrogels containing PMVE/MA/PEG 10,000 could be used for rapid delivery of drug, due to their low crosslink density. Moderately crosslinked PMVE/MA/PEG 1000 hydrogels or highly crosslinked PMVE/MA/PEG 200 systems could then be used in controlling the drug delivery rates. We are currently evaluating these systems, both alone and in combination, for use in sustained release drug delivery devices.

Investigation of swelling and network parameters of poly(ethylene glycol)-crosslinked poly(methyl vinyl ether-co-maleic acid) hydrogels

The influence of poly(ethylene glycol) (PEG) plasticiser content and molecular weight on the physicochemical properties of films cast from aqueous blends of poly(methyl vinyl ether-co-maleic acid) was investigated using thermal analysis, swelling studies, scanning electron microscopy (SEM) and attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy. FTIR spectroscopy revealed a shift of the C{double bond, long}O peak from 1708 to 1731 cm, indicating that an esterification reaction had occurred upon heating, thus producing crosslinked films. Higher molecular weight PEGs (10,000 and 1000 Da, respectively), having greater chain length, producing hydrogel networks with lower crosslink densities and higher average molecular weight between two consecutive crosslinks. Accordingly, such materials exhibited higher swelling rates. Hydrogels crosslinked with a low molecular weight PEG (PEG 200) showed rigid networks with high crosslink densities and, therefore, lower swelling rates. Polymer:plasticizer ratio alteration did not yield any discernable patterns, regardless of the method of analysis. The polymer-water interaction parameter (?) increased with increases in the crosslink density. SEM studies showed that porosity of the crosslinked films increased with increasing PEG MW, confirming what had been observed with swelling studies and thermal analysis, that the crosslink density must be decreased as the M of the crosslinker is increased. Hydrogels containing PMVE/MA/PEG 10,000 could be used for rapid delivery of drug, due to their low crosslink density. Moderately crosslinked PMVE/MA/PEG 1000 hydrogels or highly crosslinked PMVE/MA/PEG 200 systems could then be used in controlling the drug delivery rates. We are currently evaluating these systems, both alone and in combination, for use in sustained release drug delivery devices. © 2008 Elsevier Ltd. All rights reserved.

Influence of a pore-forming agent on swelling, network parameters, and permeability of poly(ethylene glycol)-crosslinked poly(methyl vinyl ether-co-maleic acid) hydrogels:Application in transdermal delivery systems

We characterized hydrogels, prepared from aqueous blends of poly(methyl vinyl ether-co-maleic acid) (PMVE/MA) and poly(ethylene glycol) (PEG 10,000 Daltons) containing a pore-forming agent (sodium bicarbonate, NaHCO ). Increase in NaHCO content increased the equilibrium water content (EWC) and average molecular weight between crosslinks (M ) of hydrogels. For example, the %EWC was 731, 860, 1109, and 7536% and the M was 8.26, 31.64, 30.04, and 3010.00 × 10 g/mol for hydrogels prepared from aqueous blends containing 0, 1, 2, and 5% w/w of NaHCO , respectively. Increase in NaHCO content also resulted in increased permeation of insulin. After 24 h, percentage permeation was 0.94, 3.68, and 25.71% across hydrogel membranes prepared from aqueous blends containing 0, 2, and 5% w/w of NaHCO , respectively. Hydrogels containing the pore-forming agent were fabricated into microneedles (MNs) for transdermal drug delivery applications by integrating the MNs with insulin-loaded patches. It was observed that the mean amount of insulin permeating across neonatal porcine skin in vitro was 20.62% and 52.48% from hydrogel MNs prepared from aqueous blends containing 0 and 5% w/w of NaHCO . We believe that these pore-forming hydrogels are likely to prove extremely useful for applications in transdermal drug delivery of biomolecules. © 2012 Wiley Periodicals, Inc.

Avian mortalities due to transmission line collisions: a review of current estimates and field methods with an emphasis on applications to the Canadian electric network

Birds are vulnerable to collisions with human-made fixed structures. Despite ongoing development and increases in infrastructure, we have few estimates of the magnitude of collision mortality. We reviewed the existing literature on avian mortality associated with transmission lines and derived an initial estimate for Canada. Estimating mortality from collisions with power lines is challenging due to the lack of studies, especially from sites within Canada, and due to uncertainty about the magnitude of detection biases. Detection of bird collisions with transmission lines varies due to habitat type, species size, and scavenging rates. In addition, birds can be crippled by the impact and subsequently die, although crippling rates are poorly known and rarely incorporated into estimates. We used existing data to derive a range of estimates of avian mortality associated with collisions with transmission lines in Canada by incorporating detection, scavenging, and crippling biases. There are 231,966 km of transmission lines across Canada, mostly in the boreal forest. Mortality estimates ranged from 1 million to 229.5 million birds per year, depending on the bias corrections applied. We consider our most realistic estimate, taking into account variation in risk across Canada, to range from 2.5 million to 25.6 million birds killed per year. Data from multiple studies across Canada and the northern U.S. indicate that the most vulnerable bird groups are (1) waterfowl, (2) grebes, (3) shorebirds, and (4) cranes, which is consistent with other studies. Populations of several groups that are vulnerable to collisions are increasing across Canada (e.g., waterfowl, raptors), which suggests that collision mortality, at current levels, is not limiting population growth. However, there may be impacts on other declining species, such as shorebirds and some species at risk, including Alberta’s Trumpeter Swans (Cygnus buccinator) and western Canada’s endangered Whooping Cranes (Grus americana). Collisions may be more common during migration, which underscores the need to understand impacts across the annual cycle. We emphasize that these estimates are preliminary, especially considering the absence of Canadian studies.

Substitution-newton-Raphson method for the solution of electric network equations

The power flow problem, in transmission networks, has been well solved, for most cases, using Newton-Raphson method (NR) and its decoupled versions. Generally speaking, the solution of a non-linear system of equations refers to two methods: NR and Successive Substitution. The proposal of this paper is to evaluate the potential of the Substitution-Newton-Raphson Method (SNR), which combines both methods, on the solution of the power flow problem. Simulations were performed using a two-bus test network in order to observe the characteristics of these methods. It was verified that the NR is faster than SNR, in terms of convergence, considering non-stressed scenarios. For those cases where the power flow in the network is closed to the limits (stressed system), the SNR converges faster. This paper presents the power flow formulation of the SNR and describes its potential for its application in special cases such as stressed scenarios. © 2006 IEEE.

A simplified method for determining the high frequency induction motor equivalent electrical circuit parameters to be used in EMI effect

The aim of this paper is to present a simple method for determining the high frequency parameters of a three-phase induction motor to be used in studies involving variable speed drives with PWM three-phase inverters, in which it is necessary to check the effects caused to the motor by the electromagnetic interference, (EMI) in the differential mode, as well as in the common mode. The motor parameters determination is generally performed in adequate laboratories using accurate instruments, such as very expensive RLC bridges. The method proposed here consists in the identification of the motor equivalent electrical circuit parameters in rated frequency and in high frequency through characteristic tests in the laboratory, together with the use of characteristic equations and curves, shown in the references to be mentioned for determining the motor high frequency parasite capacitances and also through system simulations using dedicated software, like Pspice, determining the characteristic waveforms involved in the differential and common mode phenomena, comparing and validating the procedure through published papers [01].

Numerical coupling of thermal-electric network models and energy-transport equations including optoelectronic semiconductor devices

In this work the numerical coupling of thermal and electric network models with model equations for optoelectronic semiconductor devices is presented. Modified nodal analysis (MNA) is applied to model electric networks. Thermal effects are modeled by an accompanying thermal network. Semiconductor devices are modeled by the energy-transport model, that allows for thermal effects. The energy-transport model is expandend to a model for optoelectronic semiconductor devices. The temperature of the crystal lattice of the semiconductor devices is modeled by the heat flow eqaution. The corresponding heat source term is derived under thermodynamical and phenomenological considerations of energy fluxes. The energy-transport model is coupled directly into the network equations and the heat flow equation for the lattice temperature is coupled directly into the accompanying thermal network. The coupled thermal-electric network-device model results in a system of partial differential-algebraic equations (PDAE). Numerical examples are presented for the coupling of network- and one-dimensional semiconductor equations. Hybridized mixed finite elements are applied for the space discretization of the semiconductor equations. Backward difference formluas are applied for time discretization. Thus, positivity of charge carrier densities and continuity of the current density is guaranteed even for the coupled model.

Approximate entropy of network parameters

We study the notion of approximate entropy within the framework of network theory. Approximate entropy is an uncertainty measure originally proposed in the context of dynamical systems and time series. We first define a purely structural entropy obtained by computing the approximate entropy of the so-called slide sequence. This is a surrogate of the degree sequence and it is suggested by the frequency partition of a graph. We examine this quantity for standard scale-free and Erdös-Rényi networks. By using classical results of Pincus, we show that our entropy measure often converges with network size to a certain binary Shannon entropy. As a second step, with specific attention to networks generated by dynamical processes, we investigate approximate entropy of horizontal visibility graphs. Visibility graphs allow us to naturally associate with a network the notion of temporal correlations, therefore providing the measure a dynamical garment. We show that approximate entropy distinguishes visibility graphs generated by processes with different complexity. The result probes to a greater extent these networks for the study of dynamical systems. Applications to certain biological data arising in cancer genomics are finally considered in the light of both approaches.

Analysis and comparison of network performance with different network parameters

The purpose of this study was to analyze the network performance by observing the effect of varying network size and data link rate on one of the most commonly found network configurations. Computer networks have been growing explosively. Networking is used in every aspect of business, including advertising, production, shipping, planning, billing, and accounting. Communication takes place through networks that form the basis of transfer of information. The number and type of components may vary from network to network depending on several factors such as requirement and actual physical placement of the networks. There is no fixed size of the networks and they can be very small consisting of say five to six nodes or very large consisting of over two thousand nodes. The varying network sizes make it very important to study the network performance so as to be able to predict the functioning and the suitability of the network. The findings demonstrated that the network performance parameters such as global delay, load, router processor utilization, router processor delay, etc. are affected. The findings demonstrated that the network performance parameters such as global delay, load, router processor utilization, router processor delay, etc. are affected significantly due to the increase in the size of the network and that there exists a correlation between the various parameters and the size of the network. These variations are not only dependent on the magnitude of the change in the actual physical area of the network but also on the data link rate used to connect the various components of the network.

A radial basis function network (RBFN) for function approximation

A radial basis function network (RBFN) circuit for function approximation is presented. Simulation and experimental results show that the network has good approximation capabilities. The RBFN was a squared hyperbolic secant with three adjustable parameters amplitude, width and center. To test the network a sinusoidal and sine function,vas approximated.

Gene electrotransfer into murine skeletal muscle: A systematic analysis of parameters for long-term gene expression

Skeletal muscle is an attractive target tissue for delivery of therapeutic genes, since it is well vascularized, easily accessible, and has a high capacity for protein synthesis. For efficient transfection in skeletal muscle, several protocols have been described, including delivery of low voltage electric pulses and a combination of high and low voltage electric pulses. The aim of this study was to determine the influence of different parameters of electrotransfection on short-term and long-term transfection efficiency in murine skeletal muscle, and to evaluate histological changes in the treated tissue. Different parameters of electric pulses, different time lags between plasmid DNA injection and application of electric pulses, and different doses of plasmid DNA were tested for electrotransfection of tibialis cranialis muscle of C57BI/6 mice using DNA plasmid encoding green fluorescent protein (GFP). Transfection efficiency was assessed on frozen tissue sections one week after electrotransfection using a fluorescence microscope and also noninvasively, followed by an in vivo imaging system using a fluorescence stereo microscope over a period of several months. Histological changes in muscle were evaluated immediately or several months after electrotransfection by determining infiltration of inflammatory mononuclear cells and presence of necrotic muscle fibers. The most efficient electrotransfection into skeletal muscle of C57BI/6 mice in our experiments was achieved when one high voltage (HV) and four low voltage (LV) electric pulses were applied 5 seconds after the injection of 30 μg of plasmid DNA. This protocol resulted in the highest short-term as well as long-term transfection. The fluorescence intensity of the transfected area declined after 2-3 weeks, but GFP fluorescence was still detectable 18 months after electrotransfection. Extensive inflammatory mononuclear cell infiltration was observed immediately after the electrotransfection procedure using the described parameters, but no necrosis or late tissue damage was observed. This study showed that electric pulse parameters, time lag between the injection of DNA and application of electric pulses, and dose of plasmid DNA affected the duration of transgene expression in murine skeletal muscle. Therefore, transgene expression in muscle can be controlled by appropriate selection of electrotransfection protocol.

Network approach for capturing ligand-induced subtle global changes in protein structures

Ligand-induced conformational changes in proteins are of immense functional relevance. It is a major challenge to elucidate the network of amino acids that are responsible for the percolation of ligand-induced conformational changes to distal regions in the protein from a global perspective. Functionally important subtle conformational changes (at the level of side-chain noncovalent interactions) upon ligand binding or as a result of environmental variations are also elusive in conventional studies such as those using root-mean-square deviations (r.m.s.d.s). In this article, the network representation of protein structures and their analyses provides an efficient tool to capture these variations (both drastic and subtle) in atomistic detail in a global milieu. A generalized graph theoretical metric, using network parameters such as cliques and/or communities, is used to determine similarities or differences between structures in a rigorous manner. The ligand-induced global rewiring in the protein structures is also quantified in terms of network parameters. Thus, a judicious use of graph theory in the context of protein structures can provide meaningful insights into global structural reorganizations upon perturbation and can also be helpful for rigorous structural comparison. Data sets for the present study include high-resolution crystal structures of serine proteases from the S1A family and are probed to quantify the ligand-induced subtle structural variations.

Quantum clustering and network analysis of MD simulation trajectories to probe the conformational ensembles of protein-ligand interactions

In this article, we present a novel application of a quantum clustering (QC) technique to objectively cluster the conformations, sampled by molecular dynamics simulations performed on different ligand bound structures of the protein. We further portray each conformational population in terms of dynamically stable network parameters which beautifully capture the ligand induced variations in the ensemble in atomistic detail. The conformational populations thus identified by the QC method and verified by network parameters are evaluated for different ligand bound states of the protein pyrrolysyl-tRNA synthetase (DhPylRS) from D. hafniense. The ligand/environment induced re-distribution of protein conformational ensembles forms the basis for understanding several important biological phenomena such as allostery and enzyme catalysis. The atomistic level characterization of each population in the conformational ensemble in terms of the re-orchestrated networks of amino acids is a challenging problem, especially when the changes are minimal at the backbone level. Here we demonstrate that the QC method is sensitive to such subtle changes and is able to cluster MD snapshots which are similar at the side-chain interaction level. Although we have applied these methods on simulation trajectories of a modest time scale (20 ns each), we emphasize that our methodology provides a general approach towards an objective clustering of large-scale MD simulation data and may be applied to probe multistate equilibria at higher time scales, and to problems related to protein folding for any protein or protein-protein/RNA/DNA complex of interest with a known structure.