Density evolution and power profile optimization for iterative multiuser decoders based on individually optimum multiuser detectors

Iterative multiuser joint decoding based on exact Belief Propagation (BP) is analyzed in the large system limit by means of the replica method. It is shown that performance can be improved by appropriate power assignment to the users. The optimum power assignment can be found by linear programming in most technically relevant cases. The performance of BP iterative multiuser joint decoding is compared to suboptimum approximations based on Interference Cancellation (IC). While IC receivers show a significant loss for equal-power users, they yield performance close to BP under optimum power assignment.

Optimization of PCB component placements for the collect-and-place machines

This paper presents two hybrid genetic algorithms (HGAs) to optimize the component placement operation for the collect-and-place machines in printed circuit board (PCB) assembly. The component placement problem is to optimize (i) the assignment of components to a movable revolver head or assembly tour, (ii) the sequence of component placements on a stationary PCB in each tour, and (iii) the arrangement of component types to stationary feeders simultaneously. The objective of the problem is to minimize the total traveling time spent by the revolver head for assembling all components on the PCB. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method, the nearest neighbor heuristic, and the neighborhood frequency heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different population sizes. It is proved that the performance of HGA2 is superior to HGA1 in terms of the total assembly time.

Direct real-time cavity mode assessment and optimization technique for fiber lasers

A simple technique for direct real-time assessment of a fiber laser cavity-mode condition during operation is demonstrated. Mode stabilization and optimization with this cavity-mode monitoring and conditioning feedback scheme shows significant improvements to the output performance.

Inference and optimization of real edges on sparse graphs:A statistical physics perspective

Inference and optimization of real-value edge variables in sparse graphs are studied using the Bethe approximation and replica method of statistical physics. Equilibrium states of general energy functions involving a large set of real edge variables that interact at the network nodes are obtained in various cases. When applied to the representative problem of network resource allocation, efficient distributed algorithms are also devised. Scaling properties with respect to the network connectivity and the resource availability are found, and links to probabilistic Bayesian approximation methods are established. Different cost measures are considered and algorithmic solutions in the various cases are devised and examined numerically. Simulation results are in full agreement with the theory. © 2007 The American Physical Society.

Stock selection with full-scale optimization and differential evolution

When composing stock portfolios, managers frequently choose among hundreds of stocks. The stocks' risk properties are analyzed with statistical tools, and managers try to combine these to meet the investors' risk profiles. A recently developed tool for performing such optimization is called full-scale optimization (FSO). This methodology is very flexible for investor preferences, but because of computational limitations it has until now been infeasible to use when many stocks are considered. We apply the artificial intelligence technique of differential evolution to solve FSO-type stock selection problems of 97 assets. Differential evolution finds the optimal solutions by self-learning from randomly drawn candidate solutions. We show that this search technique makes large scale problem computationally feasible and that the solutions retrieved are stable. The study also gives further merit to the FSO technique, as it shows that the solutions suit investor risk profiles better than portfolios retrieved from traditional methods.

Improving recombinant eukaryotic membrane protein yields in Pichia pastoris:the importance of codon optimization and clone selection

In the last 15 years, 80% of all recombinant proteins reported in the literature were produced in the bacterium, Escherichia coli, or the yeast, Pichia pastoris. Nonetheless, developing effective general strategies for producing recombinant eukaryotic membrane proteins in these organisms remains a particular challenge. Using a validated screening procedure together with accurate yield quantitation, we therefore wished to establish the critical steps contributing to high yields of recombinant eukaryotic membrane protein in P. pastoris. Whilst the use of fusion partners to generate chimeric constructs and directed mutagenesis have previously been shown to be effective in bacterial hosts, we conclude that this approach is not transferable to yeast. Rather, codon optimization and the preparation and selection of high-yielding P. pastoris clones are effective strategies for maximizing yields of human aquaporins.

A two-stage win–win multiattribute negotiation model:optimization and then concession

Many automated negotiation models have been developed to solve the conflict in many distributed computational systems. However, the problem of finding win-win outcome in multiattribute negotiation has not been tackled well. To address this issue, based on an evolutionary method of multiobjective optimization, this paper presents a negotiation model that can find win-win solutions of multiple attributes, but needs not to reveal negotiating agents' private utility functions to their opponents or a third-party mediator. Moreover, we also equip our agents with a general type of utility functions of interdependent multiattributes, which captures human intuitions well. In addition, we also develop a novel time-dependent concession strategy model, which can help both sides find a final agreement among a set of win-win ones. Finally, lots of experiments confirm that our negotiation model outperforms the existing models developed recently. And the experiments also show our model is stable and efficient in finding fair win-win outcomes, which is seldom solved in the existing models. © 2012 Wiley Periodicals, Inc.

Characterization and optimization of bilosomes for oral vaccine delivery

Oral vaccines offer significant benefits due to the ease of administration, better patient compliance and non-invasive, needle-free administration. However, this route is marred by the harsh gastro intestinal environment which is detrimental to many vaccine formats. To address this, a range of delivery systems have been considered including bilosomes; these are bilayer vesicles constructed from non-ionic surfactants combined with the inclusion of bile salts which can stabilize the vesicles in the gastro intestinal tract by preventing membrane destabilization. The aim of this study was to investigate the effect of formulation parameters on bilosome carriers using Design of Experiments to select an appropriate formulation to assess in vivo. Bilosomes were constructed from monopalmitoylglycerol, cholesterol, dicetyl phosphate and sodium deoxycholate at different blends ratios. The optimized bilosome formulation was identified and the potential of this formulation as an oral vaccine delivery system were assessed in biodistribution and vaccine efficacy studies. Results showed that the larger bilosomes vesicles (~6 µm versus 2 µm in diameter) increased uptake within the Peyer's patches and were able to reduce median temperature differential change and promote a reduction in viral cell load in an influenza challenge study. © 2013 Informa UK, Ltd.