Research requirements for the reduction of helicopter vibration

All prospective approaches to the reduction of helicopter vibrations were searched to establish insight for the planning of a corrective research program. The state of the art as revealed in the literature is summed up and followed by a discussion of state-of-the-art solutions and of identified technological gaps. It is applicable to all helicopters without regard to size. Extending the historic trend toward lower vibration levels will require the successful application of principles which isolate the fuselage from the rotor systems. Simplicity of the necessary isolation systems should be facilitated by providing other refinements of the dynamic design of the system

Portuguese and Brazilian stock market integration : a non-linear and detrended approach

Besides the historical heritage that Portugal and Brazil share, the last two decades have also shown an increase in some economic indicators, such as the percentage of imports/exports and foreign direct investment. In order to take advantage of all the benefits, the countries should increase economic integration, stock market integration being one of the possibilities. In this context, this paper analyses stock market integration between these two countries, using non-linear methodologies: detrended fluctuation analysis, detrended cross-correlation analysis and detrended moving-average cross-correlation analysis. Using the main stock indexes, and splitting the sample in six different periods, the main conclusion is that integration between these two countries increased over time. However, since 2013, the integration pattern has decreased, with the economic crisis both countries suffered being the main factor.info:eu-repo/semantics/publishedVersio

A statistical framework to evaluate virtual screening

<p>Abstract</p> <p>Background</p> <p>Receiver operating characteristic (ROC) curve is widely used to evaluate virtual screening (VS) studies. However, the method fails to address the "early recognition" problem specific to VS. Although many other metrics, such as RIE, BEDROC, and pROC that emphasize "early recognition" have been proposed, there are no rigorous statistical guidelines for determining the thresholds and performing significance tests. Also no comparisons have been made between these metrics under a statistical framework to better understand their performances.</p> <p>Results</p> <p>We have proposed a statistical framework to evaluate VS studies by which the threshold to determine whether a ranking method is better than random ranking can be derived by bootstrap simulations and 2 ranking methods can be compared by permutation test. We found that different metrics emphasize "early recognition" differently. BEDROC and RIE are 2 statistically equivalent metrics. Our newly proposed metric SLR is superior to pROC. Through extensive simulations, we observed a "seesaw effect" – overemphasizing early recognition reduces the statistical power of a metric to detect true early recognitions.</p> <p>Conclusion</p> <p>The statistical framework developed and tested by us is applicable to any other metric as well, even if their exact distribution is unknown. Under this framework, a threshold can be easily selected according to a pre-specified type I error rate and statistical comparisons between 2 ranking methods becomes possible. The theoretical null distribution of SLR metric is available so that the threshold of SLR can be exactly determined without resorting to bootstrap simulations, which makes it easy to use in practical virtual screening studies.</p

WISDOM-II: Screening against multiple targets implicated in malaria using computational grid infrastructures

<p>Abstract</p> <p>Background</p> <p>Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the <it>Plasmodium </it>parasite, some are promising targets to carry out rational drug discovery.</p> <p>Motivation</p> <p>Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase.</p> <p>Methods</p> <p>In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate <it>in silico </it>docking and in information technology to design and operate large scale grid infrastructures.</p> <p>Results</p> <p>On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, <it>In vitro </it>results are underway for all the targets against which screening is performed.</p> <p>Conclusion</p> <p>The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.</p

Functional Characterization of a Newly Identified Group B Streptococcus Pullulanase Eliciting Antibodies Able to Prevent Alpha-Glucans Degradation

Streptococcal pullulanases have been recently proposed as key components of the metabolic machinery involved in bacterial adaptation to host niches. By sequence analysis of the Group B Streptococcus (GBS) genome we found a novel putative surface exposed protein with pullulanase activity. We named such a protein SAP. The sap gene is highly conserved among GBS strains and homologous genes, such as PulA and SpuA, have been described in other pathogenic streptococci. The SAP protein contains two N-terminal carbohydrate-binding motifs, followed by a catalytic domain and a C-terminal LPXTG cell wall-anchoring domain. In vitro analysis revealed that the recombinant form of SAP is able to degrade α-glucan polysaccharides, such as pullulan, glycogen and starch. Moreover, NMR analysis showed that SAP acts as a type I pullulanase. Studies performed on whole bacteria indicated that the presence of α-glucan polysaccharides in culture medium up-regulated the expression of SAP on bacterial surface as confirmed by FACS analysis and confocal imaging. Deletion of the sap gene resulted in a reduced capacity of bacteria to grow in medium containing pullulan or glycogen, but not glucose or maltose, confirming the pivotal role of SAP in GBS metabolism of α-glucans. As reported for other streptococcal pullulanases, we found specific anti-SAP antibodies in human sera from healthy volunteers. Investigation of the functional role of anti-SAP antibodies revealed that incubation of GBS in the presence of sera from animals immunized with SAP reduced the capacity of the bacterium to degrade pullulan. Of interest, anti-SAP sera, although to a lower extent, also inhibited Group A Streptococcus pullulanase activity. These data open new perspectives on the possibility to use SAP as a potential vaccine component inducing functional cross-reacting antibodies interfering with streptococcal infections

Automated Docking Screens: A Feasibility Study

Molecular docking is themost practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCKBlaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCKBlaster recapitulates the crystal ligand pose within 2 A ̊ rmsd 50-60 % of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5 % of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5 % of 100 property-matched decoys while also posing within 2 A ̊ rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available a