Optimal strategies in the average consensus problem

Let a set of communicating agents compute the average of their initial positions, where every agent is restricted to communicate to a given small number of other agents (average consensus problem). We prove that the optimal topology of communication is given by a de Bruijn graph. Consensus is then reached in finitely many steps. This solution is valid when the number of agents is an exact power of the out-degree of the communication graph. We introduce an algebraic tool, the shifted Kronecker product, and a more general family of strategies, also based on a de Bruijn communication graph. Those strategies are compared to Cayley strategies in terms of the speed of convergence. We also show that quantized communication between the agents still allows finite convergence, to a consensus, which is not in general the average of the initial positions.     

A backoff strategy for model‐based experiment design under parametric uncertainty

Model‐based experiment design techniques are an effective tool for the rapid development and assessment of dynamic deterministic models, yielding the most informative process data to be used for the estimation of the process model parameters. A particular advantage of the model‐based approach is that it permits the definition of a set of constraints on the experiment design variables and on the predicted responses. However, uncertainty in the model parameters can lead the constrained design procedure to predict experiments that turn out to be, in practice, suboptimal, thus decreasing the effectiveness of the experiment design session. Additionally, in the presence of parametric mismatch, the feasibility constraints may well turn out to be violated when that optimally designed experiment is performed, leading in the best case to less informative data sets or, in the worst case, to an infeasible or unsafe experiment. In this article, a general methodology is proposed to formulate and solve the experiment design problem by explicitly taking into account the presence of parametric uncertainty, so as to ensure both feasibility and optimality of the planned experiment. A prediction of the system responses for the given parameter distribution is used to evaluate and update suitable backoffs from the nominal constraints, which are used in the design session to keep the system within a feasible region with specified probability. This approach is particularly useful when designing optimal experiments starting from limited preliminary knowledge of the parameter set, with great improvement in terms of design efficiency and flexibility of the overall iterative model development scheme. The effectiveness of the proposed methodology is demonstrated and discussed by simulation through two illustrative case studies concerning the parameter identification of physiological models related to diabetes and cancer care. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

High-performance optical fiber polarizers based on long-period gratings in birefringent optical fibers

We have demonstrated the feasibility of achieving high-performance fiber polarizers (insertion loss <0.5 dB, extinction ratio >30 dB), based on polarization mode dispersion in a long-period grating. Chirped operation with 100-nm bandwidth has also been achieved, showing the possibility of a broad-band device.     

Platform designer: An approach for modeling multiprocessor platforms based on SystemC

This paper[3.5pc] presents the Platform Designer (PD) framework, a set of SystemC based tools that provide support for modeling, simulation and analysis of multiprocessor SoC platforms (MPSoC), at different abstraction levels. PD provides mechanisms for interconnection specification, process synchronization and communication, thus allowing the modeling of a complete platform, in a unified environment. To do that it uses an extension of the ArchC ADL and acsys, a tool that enables the automatic generation of a SystemC simulator of the platform. The main advantages of this approach are twofold. First, designers have more flexibility since they can integrate and configure different processors to the platform, using a single environment. Second, it enables a faster design space exploration, given that it automatically generates SystemC simulators of whole platforms at distinct abstraction levels. A number of platform variations can be tried out with minor design changes, thus reducing design time. Experimental results show the suitability of the platform simulator for design space exploration. Real applications (with medium complexity) run in the platform in few minutes. Combined with the facility to generate platforms with minor changes, this feature allows an improvement of the design space exploration.     

Small‐Molecule Inhibitors of AF6 PDZ‐Mediated Protein–Protein Interactions

PDZ (PSD‐95, Dlg, ZO‐1) domains are ubiquitous interaction modules that are involved in many cellular signal transduction pathways. Interference with PDZ‐mediated protein–protein interactions has important implications in disease‐related signaling processes. For this reason, PDZ domains have gained attention as potential targets for inhibitor design and, in the long run, drug development. Herein we report the development of small molecules to probe the function of the PDZ domain from human AF6 (ALL1‐fused gene from chromosome 6), which is an essential component of cell–cell junctions. These compounds bind to AF6 PDZ with substantially higher affinity than the peptide (Ile‐Gln‐Ser‐Val‐Glu‐Val) derived from its natural ligand, EphB2. In intact cells, the compounds inhibit the AF6–Bcr interaction and interfere with epidermal growth factor (EGF)‐dependent signaling.     

A novel application of mesoporous silica material for extraction of pesticides

The mesoporous silica material MCM-41 was prepared by the sol-gel method and characterized using X-ray diffraction (XRD), N₂ adsorption-desorption and thermogravimetric analysis. The material was tested for extraction of trichlorfon, pyrimethanil, tetraconazole, thiabendazole, imazalil and tebuconazole from mango fruit, with analysis using gas chromatography-mass spectrometry (GC/MS). In experiments carried out in triplicate, at a 1.0 mg/kg concentration level, recoveries using the MCM-41 sorbent were in the range 73-103%. Comparison of MCM-41 with commercially available silica gel showed that MCM-41 was a similar extracting phase for the pesticides investigated with a significant cost advantage over this conventional material.     

Design and implementation of a new scheduler for enhancing multi-rate fairness in IEEE 802.16

Without the definition of a mandatory scheduling algorithm for channel resource assignment, WiMAX is open to Quality of Service (QoS) enhancements by research groups and developers, at the aim of managing heterogeneous flows with different QoS requirements. Furthermore, besides performance enhancement, another key issue arises for QoS delivery: it is known as multi-rate fairness and it deals with efficient resource allocation for providing sufficient bandwidth to high rate flows, without penalizing low rate ones. In this paper, uplink scheduling algorithms are studied and an innovative solution is proposed to achieve performance enhancement, multi-rate fairness and improved QoS management. After an overview of the state of the art, two scheduling algorithms based on Deficit Round Robin are studied, implemented and tested in NS2 simulator. The schedulers are validated and compared through exhaustive simulations, showing the benefits coming from the adoption of the proposed scheduling mechanism.     

Monitoring the bacterial population dynamics during fermentation of artisanal Argentinean sausages

The dynamics of the microbial community responsible for the artisanal fermentation of dry sausage produced in Argentina was investigated by using classical and molecular approaches. The combined use of RAPD analysis with primers M13, XD9, RAPD1 and RAPD2 and 16S rDNA sequencing were applied to the identification and intraspecific differentiation of 100 strains of lactobacilli and Micrococcaceae. DGGE analysis was used to monitor the dynamic changes in population after total microbial DNA was directly extracted from sausages and subjected to PCR using V3f (GC), Bact-0124f-GC and Univ-0515r primers. The sequence analysis of 16S rDNA of the dominant species was also carried out. Lactobacillus sakei and Lactobacillus plantarum were the dominant lactic acid organisms during the fermentation while Staphylococcus saprophyticus represented the dominant species of Micrococcaceae. It was demonstrated that the ripening process of Argentinean artisanal fermented sausage is driven by a limited number of Lactobacillus and Staphylococcus strains selected from environmental microbiota by the ability to best compete under the prevailing conditions of the ecological niche. The identification of dominant communities present in this artisanal fermented sausage can help in the selection of starter cultures consisting in well adapted strains to the particular production technology.