"Parallel" and "antiparallel tail-clamps" increase the efficiency of triplex formation with structured DNA and RNA targets

Sequence-specific triple-helix structures can be formed by parallel and antiparallel DNA clamps interacting with single-stranded DNA or RNA targets. Single-stranded nucleic acid molecules are known to adopt secondary structures that might interfere with intermolecular interactions. We demonstrate the correlation between a secondary structure involving the target--a stable stem predicted by in silico folding and experimentally confirmed by thermal stability and competition analyses--and an inhibitory effect on triplex formation. We overcame structural impediments by designing a new type of clamp: "tail-clamps". A combination of gel-shift, kinetic analysis, UV thermal melting and thermodynamic techniques was used to demonstrate that tail-clamps efficiently form triple helices with a structured target sequence. The performance of parallel and antiparallel tail-clamps was compared: antiparallel tail-clamps had higher binding efficiencies than parallel tail-clamps both with structured DNA and RNA targets. In addition, the reported triplex-stabilizing property of 8-aminopurine residues was confirmed for tail-clamps. Finally, we discuss the possible use of this improved triplex technology as a new tool for applications in molecular biology.     

Synthesis of oligodeoxynucleotides containing N4-mercaptoethylcytosine and their use in the preparation of oligonucleotide-peptide conjugates carrying c-myc tag-sequence

This study was designed to evaluate the effectiveness of zinc sulphate both in vitro and in an animal model against both strains of old world cutaneous leishmaniasis. The in vitro sensitivities of promastigotes and axenic amastigotes of both Leishmania major and L. tropica to zinc sulphate was determined, the LD50 calculated and compared to the standard treatment for cutaneous leishmaniasis pentavalent antimony compounds. The results show that the two forms of both strains were sensitive to zinc sulphate and their respective LD50 were lower compared to the pentavalent antimony compound. Furthermore the sensitivities of the forms of both strains were tested using a simple slide method and compared to results of the standard method. To confirm this result, zinc sulphate was administered orally to mice infected with cutaneous leishmaniasis both therapeutically and prophylactically. Results showed that oral zinc sulphate was effective in both treatment and prophylaxis for cutaneous leishmaniasis. These results encourage the use of oral zinc sulphate in the treatment of cutaneous leishmaniasis clinically.     

Graph kernels and Gaussian processes for relational reinforcement learning

RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no natural representation as a tuple of constants. For relational reinforcement learning, the learning algorithm used to approximate the mapping between state-action pairs and their so called Q(uality)-value has to be very reliable, and it has to be able to handle the relational representation of state-action pairs. In this paper we investigate the use of Gaussian processes to approximate the Q-values of state-action pairs. In order to employ Gaussian processes in a relational setting we propose graph kernels as a covariance function between state-action pairs. The standard prediction mechanism for Gaussian processes requires a matrix inversion which can become unstable when the kernel matrix has low rank. These instabilities can be avoided by employing QR-factorization. This leads to better and more stable performance of the algorithm and a more efficient incremental update mechanism. Experiments conducted in the blocks world and with the Tetris game show that Gaussian processes with graph kernels can compete with, and often improve on, regression trees and instance based regression as a generalization algorithm for RRL. Editors: David Page and Akihiro Yamamoto     

Consistency of SLAM-EKF Algorithms for Indoor Environments

The solution to the Simultaneous Localization And Mapping (SLAM) problem using an Extended Kalman Filter (EKF) is probably the most extended in the literature despite the recently reported inconsistency of its estimation. There has been an important lack of successful SLAM-EKF implementations for indoor environments that could build monolithic large maps with features conveying angular information. In this paper we analyze the source and factors of the SLAM-EKF inconsistency in indoor environments (where the landmarks contain angular information) and we review current existing approaches presenting novel solutions to this problem that let us build indoor large monolithic feature based maps.     

Collaborative e-Government: impediments and benefits of information-sharing projects in the public sector

Information-sharing projects are becoming increasingly important in both public and private organizations. Generally, organizations base their decision to move forward with an information-sharing project on the project's expected benefits such as better services, operational savings, and increased program effectiveness. Clearly, potential impediments particular to the government environment could limit the attainment of benefits, jeopardizing the project's business case and even the project itself. Yet, we know very little about how users’ perceived impediments affect a project's expected benefits in collaborative digital government initiatives. Using data from six public sector information-sharing projects, this paper reveals how some managerial and cultural impediments (e.g., control-oriented management) limit perceptions of expected benefits. Surprisingly, political impediments were not found to significantly affect the expectations of benefits. Additionally, the paper provides managers with specific advice on how to better understand users’ perceptions and expectations. The paper should be of interest to both academicians and practitioners who are interested in government information technology implementation, in general, and collaborative e-Government, in particular.     

Atmospheric particulate matter (PM) estimation from SeaWiFS imagery

Air quality monitoring by satellite imagery is a potential complementary tool to in-situ measurements. Deriving particulate matter (PM) from the satellite derived aerosol optical thickness (AOT) is not straightforward. The relation between the two quantities is not explicit or, if so, too many unknowns exist. The idea, proposed by Pelletier et al. [Pelletier, B., Santer, R., & Vidot, J. (in press). Retrieving of particulate matter from optical measurements: A semiparametric approach. Journal of Geophysical Research, 112. doi:10.1029/2005JD006737], is to involve in the associations PM-AOT auxiliary meteorological information using a statistical approach. We use this method first on optical ground measurements and second on SeaWiFS imagery in the framework of a regional European project. A SeaWiFS archive was processed both over land and over ocean to produce AOT. A database was developed to associate locally and daily SeaWiFS AOT and PM. A part of this database was used to train the statistical method; another part of it was used for validation. Results are promising. Overall, the method allows retrieving the PM10 with a coefficient of determination of 0.42 and the PM2.5 with a coefficient of determination of 0.48. The outputs of this work are PM10 SeaWiFS maps and a limited comparison with in-situ data is reported.     

An efficient iterated local search algorithm for the total tardiness blocking flow shop problem

This paper deals with the blocking flow shop problem and proposes an Iterated Local Search (ILS) procedure combined with a variable neighbourhood search (VNS) for the total tardiness minimisation. The proposed ILS makes use of a NEH-based procedure to generate the initial solution, and uses a local search to intensify the exploration that combines the insertion and swap neighbourhood and uses a perturbation mechanism consisting of three neighbourhood operators to diversify the search. The computational evaluation has shown the effectiveness of combining the insertion and swap neighbourhood during the search despite the insertion neighbourhood being more effective than the swap neighbourhood for this problem. Finally, the computation of this algorithm when evaluated against two other algorithms from the literature shows good performance.     

Development of delta ferrite on the weld and HAZ produced by pulsed plasma arc welding on a supermartensitic stainless steel

Delta ferrite is considered an undesirable phase in the microstructure of martensitic stainless steels, given its power to influence the performance of fatigue strength, toughness and corrosion under stress. This study aimed to investigate the effect of pulsed plasma welding on the distribution and amount of delta ferrite on a supermartensitic stainless steel (SMSS). Weld beads were obtained by surface melting on a sample of SMSS alloy using conventional and pulsed current. Then, the microstructural characterization was performed, in particular of the delta ferrite via metallographic analyses by optical and scanning electron microscopy. The experiments showed that for the same heat input, the pulse current promoted the formation of delta ferrite in the form of bands along the weld bead and a significant reduction of this phase in the heat-affected zone compared to conventional welding.