How Does the Spacer Length of Cationic Gemini Lipids Influence the Lipoplex Formation with Plasmid DNA? Physicochemical and Biochemical Characterizations and their Relevance in Gene Therapy

Lipoplexes formed by the pEGFP-C3 plasmid DNA (pDNA) and lipid mixtures containing cationic gemini surfactant of the 1,2-bis(hexadecyl dimethyl ammonium) Acmes family referred to as C16CnC16, where n = 2 3, 5, or 12, and the zwitterionic helper lipid, 1,2-dioleoyl-sn-glycero-3-phosphatidylethanolamine (DOPE) have been studied from a wide variety of physical, chemical, and biological standpoints. The study has been carried out using several experimental methods, such as zeta potential, gel electrophoresis, small-angle X-ray scattering (SAXS), cryo-TEM, gene transfection, cell viability/cytotoxicity, and confocal fluorescence microscopy. As reported recently in a communication (J. Am. Chem. Soc. 2011, 133, 18014), the detailed physicochemical and biological studies confirm that, in the presence of the studied series lipid mixtures, plasmid DNA is compacted with a large number of its associated Na+ counterions. This in turn yields a much lower effective negative charge, q(pDNA)(-), a value that has been experimentally obtained for each mixed lipid mixture. Consequently, the cationic lipid (CL) complexes prepared with pDNA and CL/DOPE mixtures to be used in gene transfection require significantly less amount of CL than the one estimated assuming a value of q(DNA)(-) = -2. This drives to a considerably lower cytotoxicity of the gene vector. Depending on the CL molar composition, alpha, of the lipid mixture, and the effective charge ratio of the lipoplex, rho(eff), the reported SAXS data indicate the presence of two or three structures in the same lipoplex, one in the DOPE-rich region, other in the CL-rich region, and another one present at any CL composition. Cryo-TEM and SAXS studies with C16CnC16/DOPE-pDNA lipoplexes indicate that pDNA is localized between the mixed lipid bilayers of lamellar structures within a monolayer of similar to 2 nm. This is consistent with a highly compacted supercoiled pDNA conformation compared with that of linear DNA. Transfection studies were carried out with HEK293T, HeLa, CHO, U343, and H460 cells. The alpha and rho(eff) values for each lipid mixture were optimized on HEK293T cells for transfection, and using these values, the remaining cells were also transfected in absence (-FBS-FBS) and presence (-FBS+FBS) of serum. The transfection efficiency was higher with the CLs of shorter gemini spacers (n = 2 or 3). Each formulation expressed GFP on pDNA transfection and confocal fluorescence microscopy corroborated the results. C16C2C16/DOPE mixtures were the most efficient toward transfection among all the lipid mixtures and, in presence of serum, even better than the Lipofectamine2000, a commercial transfecting agent Each lipid combination was safe and did not show any significant levels of toxicity. Probably, the presence of two coexisting lamellar structures in lipoplexes synergizes the transfection efficiency of the lipid mixtures which are plentiful in the lipoplexes formed by CLs with short spacer (n = 2, 3) than those with the long spacer (n = 5, 12).

Methodology for Pavement Design Reliability and Back Analysis Using Markov Chain Monte Carlo Simulation

Given the increasing cost of designing and building new highway pavements, reliability analysis has become vital to ensure that a given pavement performs as expected in the field. Recognizing the importance of failure analysis to safety, reliability, performance, and economy, back analysis has been employed in various engineering applications to evaluate the inherent uncertainties of the design and analysis. The probabilistic back analysis method formulated on Bayes' theorem and solved using the Markov chain Monte Carlo simulation method with a Metropolis-Hastings algorithm has proved to be highly efficient to address this issue. It is also quite flexible and is applicable to any type of prior information. In this paper, this method has been used to back-analyze the parameters that influence the pavement life and to consider the uncertainty of the mechanistic-empirical pavement design model. The load-induced pavement structural responses (e.g., stresses, strains, and deflections) used to predict the pavement life are estimated using the response surface methodology model developed based on the results of linear elastic analysis. The failure criteria adopted for the analysis were based on the factor of safety (FOS), and the study was carried out for different sample sizes and jumping distributions to estimate the most robust posterior statistics. From the posterior statistics of the case considered, it was observed that after approximately 150 million standard axle load repetitions, the mean values of the pavement properties decrease as expected, with a significant decrease in the values of the elastic moduli of the expected layers. An analysis of the posterior statistics indicated that the parameters that contribute significantly to the pavement failure were the moduli of the base and surface layer, which is consistent with the findings from other studies. After the back analysis, the base modulus parameters show a significant decrease of 15.8% and the surface layer modulus a decrease of 3.12% in the mean value. The usefulness of the back analysis methodology is further highlighted by estimating the design parameters for specified values of the factor of safety. The analysis revealed that for the pavement section considered, a reliability of 89% and 94% can be achieved by adopting FOS values of 1.5 and 2, respectively. The methodology proposed can therefore be effectively used to identify the parameters that are critical to pavement failure in the design of pavements for specified levels of reliability. DOI: 10.1061/(ASCE)TE.1943-5436.0000455. (C) 2013 American Society of Civil Engineers.

Non-Stationary Semi-Markov Decision Processes on a Finite Horizon

We introduce and study a class of non-stationary semi-Markov decision processes on a finite horizon. By constructing an equivalent Markov decision process, we establish the existence of a piecewise open loop relaxed control which is optimal for the finite horizon problem.

Nodal length fluctuations for arithmetic random waves

Using the spectral multiplicities of the standard torus, we endow the Laplace eigenspaces with Gaussian probability measures. This induces a notion of random Gaussian Laplace eigenfunctions on the torus (''arithmetic random waves''). We study the distribution of the nodal length of random eigenfunctions for large eigenvalues, and our primary result is that the asymptotics for the variance is nonuniversal. Our result is intimately related to the arithmetic of lattice points lying on a circle with radius corresponding to the energy.

Quantum phases of dimerized and frustrated Heisenberg spin chains with s=1/2, 1 and 3/2: an entanglement entropy and fidelity study

We study here different regions in phase diagrams of the spin-1/2, spin-1 and spin-3/2 one-dimensional antiferromagnetic Heisenberg systems with frustration (next-nearest-neighbor interaction J(2)) and dimerization (delta). In particular, we analyze the behaviors of the bipartite entanglement entropy and fidelity at the gapless to gapped phase transitions and across the lines separating different phases in the J(2)-delta plane. All the calculations in this work are based on numerical exact diagonalizations of finite systems.

On the mechanism and the length scales involved in the ductile fracture of a bulk metallic glass

Some bulk metallic glasses (BMGs) exhibit high crack initiation toughness due to shear band mediated plastic flow at the crack tip and yet do not display additional resistance to crack growth due to the lack of a microstructure. Thus, at crack initiation, the fracture behavior of BMGs transits from that of ductile alloys to that of brittle ceramics. In this paper, we attempt to understand the physics behind the characteristic length from the notch root at which this transition occurs, through testing of four-point bend specimens made of a nominally ductile Zr-based BMG in three different structural states. In the as-cast state, both symmetric (mode I) and asymmetric (mixed mode) bend specimens are tested. The process of shear band mediated plastic flow followed by crack initiation at the notch root was monitored through in situ imaging. Results show that stable crack growth occurs inside a dominant shear band through a distance of, similar to 60 mu m, irrespective of the structural state and mode mixity, before attaining criticality. Detailed finite element simulations show that this length corresponds to the distance from the notch root over which a positive hydrostatic stress gradient prevails. The mean ridge heights on fractured surfaces are found to correlate with the toughness of the BMG. The Argon and Salama model, which is based on the meniscus instability phenomenon at the notch root, is modified to explain the experimentally observed physics of fracture in ductile BMGs. (C) 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Effect of resonator length and working fluid on the performance of twin thermoacoustic heat engine - experimental and simulation studies

Success in the advancement of thermoacoustic field led the researchers to develop the thermoacoustic engines which found its applications in various fields such as refrigeration, gas mixture separation, natural gas liquefaction, and cryogenics. The objective of this study is to design and fabricate the twin thermoacoustic heat engine (TAHE) producing the acoustic waves with high resonance frequencies which is used to drive a thermoacoustic refrigerator efficiently by the influence of geometrical parameters and working fluids. Twin TAHE has gained significant attention due to the production of high intensity acoustic waves than single TAHE. In order to drive an efficient thermoacoustic refrigerator, a twin thermoacoustic heat engine is built up and its performance are analysed by varying the resonator length and working fluid. The performance is measured in terms of onset temperature difference, resonance frequency and pressure amplitude of the oscillations generated from twin TAHE. The simulation is performed using free software DeltaEC, from LANL, USA. The simulated DeltaEC results are compared with experimental results and the deviations are found within +10%.

Charge transport and magnetic properties of coaxial composite fibrils of polypyrrole/multiwall carbon nanotubes at low temperature

We report the low temperature electrical and magnetic properties of polypyrrole (PPy)/multiwall carbon nanotube (MWNT) coaxial composite fibrils synthesized by the electro-polymerization method. The iron-filled MWNTs were first grown by chemical vapor deposition of a mixture of liquid phase organic compound and ferrocene by the one step method. Then the PPy/MWNT fibrils were prepared by the electrochemical polymerization process. Electron microscopy studies reveal that PPy coating on the surface of nanotube is quite uniform throughout the length. The temperature dependent electrical resistivity and magnetization measurements were done from room temperature down to 5 and 10 K, respectively. The room temperature resistivity (rho) of PPy/MWNT composite fibril sample is similar to 3.8 Omega m with resistivity ratio R-5 K/R-300 K] of similar to 300, and the analysis of rho(T) in terms of reduced activation energy shows that resistivity lies in the insulating regime below 40 K. The resistivity varies according to three dimensional variable range hopping mechanism at low temperature. The magnetization versus applied field (M-H loop) data up to a field of 20 kOe are presented, displaying ferromagnetic behavior at all temperatures with enhanced coercivities similar to 680 and 1870 Oe at room temperature and 10 K, respectively. The observation of enhanced coercivity is due to significant dipolar interaction among encapsulated iron nanoparticles, and their shape anisotropy contribution as well.

Performance improvement of short-length regular low-density parity-check codes with low-complexity post-processing

It is well known that extremely long low-density parity-check (LDPC) codes perform exceptionally well for error correction applications, short-length codes are preferable in practical applications. However, short-length LDPC codes suffer from performance degradation owing to graph-based impairments such as short cycles, trapping sets and stopping sets and so on in the bipartite graph of the LDPC matrix. In particular, performance degradation at moderate to high E-b/N-0 is caused by the oscillations in bit node a posteriori probabilities induced by short cycles and trapping sets in bipartite graphs. In this study, a computationally efficient algorithm is proposed to improve the performance of short-length LDPC codes at moderate to high E-b/N-0. This algorithm makes use of the information generated by the belief propagation (BP) algorithm in previous iterations before a decoding failure occurs. Using this information, a reliability-based estimation is performed on each bit node to supplement the BP algorithm. The proposed algorithm gives an appreciable coding gain as compared with BP decoding for LDPC codes of a code rate equal to or less than 1/2 rate coding. The coding gains are modest to significant in the case of optimised (for bipartite graph conditioning) regular LDPC codes, whereas the coding gains are huge in the case of unoptimised codes. Hence, this algorithm is useful for relaxing some stringent constraints on the graphical structure of the LDPC code and for developing hardware-friendly designs.

A novel Q-learning algorithm with function approximation for constrained Markov decision processes

We present a novel multi-timescale Q-learning algorithm for average cost control in a Markov decision process subject to multiple inequality constraints. We formulate a relaxed version of this problem through the Lagrange multiplier method. Our algorithm is different from Q-learning in that it updates two parameters - a Q-value parameter and a policy parameter. The Q-value parameter is updated on a slower time scale as compared to the policy parameter. Whereas Q-learning with function approximation can diverge in some cases, our algorithm is seen to be convergent as a result of the aforementioned timescale separation. We show the results of experiments on a problem of constrained routing in a multistage queueing network. Our algorithm is seen to exhibit good performance and the various inequality constraints are seen to be satisfied upon convergence of the algorithm.