Self-managed topologies in P2P networks

The problem of efficient resource location is an important open issue in P2P systems. This paper introduces DANTE, a self-adapting P2P system that changes its peer links to form topologies where resources are located in an efficient manner via random walks. Additionally, this same self-adaptation capacity makes DANTE capable of reacting to events like changes in the system load or attacks on well-connected nodes by adjusting the topology to the new scenario. This adaptive behavior emerges as the global result of the individual work of nodes, without the intervention of any central entity or the need for global knowledge. Simulations show that this adaptation process makes the system scalable, resilient to attacks, and tolerant to a high transitivity of peers. Simulations are also used to compare this solution with other well-known self-adapting P2P system. From these results it can be concluded that the topologies achieved by DANTE offer better performance.     

AC electrokinetic pumping on symmetric electrode arrays

AC electro-osmotic (ACEO) pumping is experimentally demonstrated on a symmetric gold electrode array. Using asymmetric connection of electrodes to the applied AC voltage, spatial asymmetry along the array is created, which produces unidirectional flow of electrolyte. An aqueous solution of 100 μM KCl is selected as the pumping fluid. The liquid velocity obtained as a function of voltage and frequency is compared to that generated using travelling-wave electroosmosis (TWEO) with the same electrode array. The expected velocities from the linear electrokinetic models of ACEO and TWEO are computed numerically. The comparison shows that TWEO generates greater velocity amplitudes and the streamlines are smoother than those generated by ACEO.     

Charting online OMICS resources: A navigational chart for clinical researchers

The life sciences have sprouted several popular and successful OMICS technologies that span all levels of biological information transfer. Ever since the start of the Human Genome Project, the then revolutionary idea to make all resulting data publicly available has been central to all of the efforts across OMICS technologies. As a result, a great variety of publicly available data repositories and resources is currently available to the research community. This widespread availability of data does come at the price of increased confusion on the part of the users, especially for those that see the OMICS technologies as tools to help unravel a larger biological or clinical question. We therefore provide a comprehensive overview of the available resources across OMICS fields, with a special emphasis on those databases that are relevant to the study of proteins. Additionally, we also describe various integrative systems that have been established, and highlight new developments in the field that can revolutionize the way in which live data integration is achieved over the internet.     

The anti-reflective algebra: structural and computational analysis with application to image deblurring and denoising

Anti-reflective (AR) boundary conditions (BC) have been introduced recently in connection with fast deblurring algorithms, both in the case of signals and images. Here we extend such BCs to d dimensions (d ≥ 1) and we study in detail the algebra induced by the AR-BCs, with strongly symmetric point spread functions (PSF), both from a structural and computational point of view. The use of the re-blurring idea and the computational features of the AR-algebra allow us to apply Tikhonov-like techniques within O(n ^d log(n)) arithmetic operations, where n ^d is the number of pixels of the reconstructed object. Extensive numerical experimentation concerning 2D images and strongly symmetric PSFs confirms the effectiveness of our proposal.      

Simple tests for multi-criteria optimality

In this paper we present two tests which can decide whether a given pointx ₀ ^N is locally efficient or not with respect to a given finite set of real valued continuously differentiable functions defined on ^N . Examples indicate that the tests may fail on a nowhere dense set.     

Recent Advances on High-Speed and Holographic Two-Photon Direct Laser Writing

Two-Photon Lithography, thanks to its very high sub-diffraction resolution, has become the lithographic technique par excellence in applications requiring small feature sizes and complex 3D pattering. Despite this, the fabrication times required for extended structures remain much longer than those of other competing techniques (UV mask lithography, nanoimprinting, etc.). Its low throughput prevents its wide adoption in industrial applications. To increase it, over the years different solutions have been proposed, although their usage is difficult to generalize and may be limited depending on the specific application. A promising strategy to further increase the throughput of Two-Photon Lithography, opening a concrete window for its adoption in industry, lies in its combination with holography approaches: in this way it is possible to generate dozens of foci from a single laser beam, thus parallelizing the fabrication of periodic structures, or to engineer the intensity distribution on the writing plane in a complex way, obtaining 3D microstructures with a single exposure. Here, the fundamental concepts behind high-speed Two-Photon Lithography and its combination with holography are discussed, and the literary production of recent years that exploits such techniques is reviewed, and contextualized according to the topic covered.     

Bacteria-Responsive Self-Assembly of Antimicrobial Peptide Nanonets for Trap-and-Kill of Antibiotic-Resistant Strains

Bacterial trapping using nanonets is a ubiquitous immune defense mechanism against infectious microbes. These nanonets can entrap microbial cells, effectively arresting their dissemination and rendering them more vulnerable to locally secreted microbicides. Inspired by this evolutionarily conserved anti-infective strategy, a series of 15 to 16 residue-long synthetic β-hairpin peptides is herein constructed with the ability to self-assemble into nanonets in response to the presence of bacteria, enabling spatiotemporal control over microbial killing. Using amyloid-specific K114 assay and confocal microscopy, the membrane components lipoteichoic acid and lipopolysaccharide are shown to play a major role in determining the amyloid-nucleating capacity as triggered by Gram-positive and Gram-negative bacteria respectively. These nanonets displayed both trapping and killing functionalities, hence offering a direct improvement from the trap-only biomimetics in literature. By substituting a single turn residue of the non-amyloidogenic BTT1 peptide, the nanonet-forming BTT1-3A analog is produced with comparable antimicrobial potency. With the same sequence manipulation approach, BTT2-4A analog modified from BTT2 peptide showed improved antimicrobial potency against colistin-resistant clinical isolates. The peptide nanonets also demonstrated robust stability against proteolytic degradation, and promising in vivo efficacy and biosafety profile. Overall, these bacteria-responsive peptide nanonets are promising clinical anti-infective alternatives for circumventing antibiotic resistance.     

Experience report on the application of genetic algorithms to reduce costs of the software validation process in the automotive sector during an engine control unit project

Software Quality Journal - The number of electronic control units (ECU) installed in vehicles is increasingly high. Manufacturers must improve the software quality and reduce cost by proposing...     

Design Optimization of Composite Prosthetic Tubes Using GA-ANN Algorithm Considering Tsai-Wu Failure Criteria

The investigation of possible failures in composite materials is a matter of very great importance, and the Tsai-Wu criterion is an effective criterion for analyzing those flaws in anisotropic materials and defining whether the material at a given load will or will not suffer structural failure. In this study, an optimization procedure is proposed to minimize the maximum value of Tsai-Wu of laminated composite tubes subject to axial loading. Artificial neural networks and genetic algorithms are chosen as optimization tools. The results of this study show that the developed algorithm converges faster. Then, the maximum Tsai-Wu value is used as the objective function and the fiber orientations are the constraints in the optimization process. The results yielded by them are compared and discussed. Optimal results are compared with respect to the usual initial design. The design approach is recommended for structures where composites are the key load-carrying members such as orthopedic prosthesis.