Evaluation de la charge virale dans les eaux d''une station d''epuration biologique au moyen de deux methodes de concentration de virus par adsorption-elution sur poudre de verre ou sur microfibre de verre

Two methods of adsorption-elution on glass powder or on glass microfibre have allowed to determine the virus quantity at the entrance and at the exit of a biologic sewage farm. Almost the same results are obtained by comparing the two techniques. The frequency of virus isolation is very important both in the affluent and in the effluent. The rate of reducing the quantity of virus in the effluent is in the region of 78%. The identification of the virus has shown the systematic existence of Enterovirus. If one has to choose between the two techniques, the method of adsorption-elution on glass powder is more advisable, because there is no problem of blockage.     

An iterated local search heuristic for multi-capacity bin packing and machine reassignment problems

This paper proposes an efficient Multi-Start Iterated Local Search for Packing Problems (MS-ILS-PPs) metaheuristic for Multi-Capacity Bin Packing Problems (MCBPP) and Machine Reassignment Problems (MRP). The MCBPP is a generalization of the classical bin-packing problem in which the machine (bin) capacity and task (item) sizes are given by multiple (resource) dimensions. The MRP is a challenging and novel optimization problem, aimed at maximizing the usage of available machines by reallocating tasks/processes among those machines in a cost-efficient manner, while fulfilling several capacity, conflict, and dependency-related constraints. The proposed MS-ILS-PP approach relies on simple neighborhoods as well as problem-tailored shaking procedures. We perform computational experiments on MRP benchmark instances containing between 100 and 50,000 processes. Near-optimum multi-resource allocation and scheduling solutions are obtained while meeting specified processing-time requirements (on the order of minutes). In particular, for 9/28 instances with more than 1000 processes, the gap between the solution value and a lower bound measure is smaller than 0.1%. Our optimization method is also applied to solve classical benchmark instances for the MCBPP, yielding the best known solutions and optimum ones in most cases. In addition, several upper bounds for non-solved problems were improved.     

Optimization of the formation of vinyldithiins, therapeutic compounds from garlic

Allyl sulfides, ajoenes and vinyldithiins are the three main groups of volatile organosulfur compounds that are formed when garlic is crushed. The manner garlic is processed (nature of the extraction medium, temperature…) has a major influence on their relative proportion and the amounts produced. It has been proven recently that the vinyldithiins are at the origin of garlic’s capacity to prevent adipocytes development. Their incorporation in garlic-based nutraceuticals is thus particularly interesting. In this context, this work aims to optimize the production of vinyldithiins from garlic. After having determined the best garlic origin (Spanish) and the best oil for the extraction (olive or sunflower oil), the extraction conditions were optimized (1/2 (w/w garlic oil), 37 °C, 6 h) and 133 mg of vinyldithiins was obtained from 100 g of fresh garlic. Carrying out the extraction under microwave irradiation allowed increasing the yield 3.6-fold (yield 486 mg of vinyldithiins from 100 g of fresh garlic). This study may also contribute to the development of new garlic derived high value products by enhancing the comprehension of their formation.     

The Gestalt heuristic: emerging abstraction to improve combinatorial search

Nowadays, many engineering applications require the minimization of a cost function such as decreasing the delivery time or the used space, reducing the development effort, and so on. Not surprisingly, research in optimization is one of the most active fields of computer science. Metaheuristics are part of the state-of-the-art techniques for combinatorial optimization. But their success comes at the price of considerable efforts in design and development time. Can we go further and automate their preparation? Especially when time is limited, dedicated techniques are unknown or the tackled problem is not well understood? The Gestalt heuristic, a search based on meta-modeling, answers those questions. Our approach, inspired by Gestalt psychology, considers the problem representation as a key factor of the success of the metaheuristic search process. Thanks to the emergence of such representation abstraction, the metaheuristic is being assisted by constraining the search. This abstraction is mainly based on the aggregation of the representation variables. The metaheuristic operators then work with these new aggregates. By learning, the Gestalt heuristic continuously searches for the right level of abstraction. It turns out to be an engineering mechanism very much related with the intrinsic emergence concept. First, the paper introduces the approach in the practical context of combinatorial optimization. It describes one possible implementation with evolutionary algorithms. Then, several experimental studies and results are presented and discussed in order to test the suggested Gestalt heuristic implementation and its main characteristics. Finally, the heuristic is more conceptually discussed in the context of emergence.     

DDCA-WSN: A Distributed Data Compression and Aggregation Approach for Low Resources Wireless Sensors Networks

Wireless Sensor Networks (WSN) have been as useful and beneficial as resource-constrained distributed event-based system for several scenarios. Yet, in WSN, optimisation of limited resources (energy, computing memory, bandwidth and storage) during data collection and communication process is a major challenge. Data redundancy involves a large consumption of sensor resources during processing and transferring information to an analysis centre. As a matter of fact, most of energy consumption (as much as 80%) for standard WSN applications lies in the radio module where receiving and sending packets is necessary to communicate between stations.  Thus, this paper proposes an approach to achieve optimal sensor resources by data compression and aggregation regarding integrity of raw data. Then, the main objective is to reduce this redundancy by discarding a certain number of packets of information and keeping only the most meaningful and informative ones for the reconstruction. Data aggregation discarded a certain sensing data packet, which lead to low data-rate communication and low likelihood of packet collisions on the wireless medium. Data compression reduces a redundancy in keeping aggregated data, in order to diminish resources consumption of wireless sensor nodes, which leads to storage saving and sending only a small data stream in the bandwidth of communication. The performances of the proposed approach DDCA-WSN are qualified using experimental simulation on OMNeT++/Castalia. The performance metrics were evaluated in terms of Compression Ratio (CR), data Aggregation Rate (AR), Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE) and Energy Consumption (EC).The obtained results have significantly increased the network lifetime. Moreover, the integrity (quality) of the raw data is guaranteed.

     

Quantum relays for long distance quantum cryptography

Quantum cryptography is on the verge of commercial application. One of its greatest limitations is over long distance—secret key rates are low and the longest fibre over which any key has been exchanged is currently 100km. We investigate the quantum relay, which can increase the maximum distance at which quantum cryptography is possible. The relay splits the channel into sections and sends a different photon across each section, increasing the signal-to-noise ratio. The photons are linked as in teleportation, with entangled photon pairs and Bell measurements. We show that such a scheme could allow cryptography over hundreds of kilometres with today's detectors. It could not, however, improve the rate of key exchange over distances where the standard single section scheme already works. We also show that reverse key reconciliation, previously used in continuous variable quantum cryptography, gives a secure key over longer distances than forward key reconciliation.     

Increasing the lateral resolution of 4Pi fluorescence microscopes

The axial resolution of fluorescence microscopes can be considerably improved by superposing two illumination beams and by adding coherently the two wavefronts emitted by the luminescent sample. This solution has been implemented in 4Pi microscopes. Theoretical and experimental results have shown that a considerable improvement of the axial resolution can be obtained with these microscopes. However, the lateral resolution remains limited by diffraction. We propose a configuration of a 4Pi microscope in which the lateral displacement of the source modifies the collection efficiency function (CEF). Numerical calculations based on an approximate scalar theory and on exact vector-wave-optics results of the field distribution of the electromagnetic field in image space show that the lateral extent of the CEF can be reduced by a factor greater than 2 with respect to the diffraction limit. We show that, with this solution, the resolution in the transverse plane of 4Pi type B and 4Pi type C microscopes can be improved significantly.     

Electrical characterisation of p-doped distributed Bragg reflectors in electrically pumped GaInNAs VCSOAs for 1.3 μm operation

The high resistivity that is encountered in p-type DBRs is an important problem in vertical cavity surface emitting lasers and optical amplifiers (VCSELs and VCSOAs). This is because the formation of potential barriers at the interfaces between layers of high and low refractive index inhibits the carrier flow, thus increasing the DBR series resistance. In this work, the electrical characteristics of two p-type doped DBR structures grown on undoped and p-type doped GaAs substrates have been investigated. The DBRs are designed for VCSOAs operating at 1.3 μm and consist of 14-periods of alternating GaAs and Al_0.9Ga_0.1As in the first sample and 14-periods of GaAs and Al_0.3Ga_0.7As/Al_0.9Ga_0.1As in the second one. For the longitudinal transport sample, Hall mobility and sheet carrier density were measured in the temperature range from 77 to 300 K. In the vertical transport sample, current–voltage (I–V) measurements across the DBR layers were carried out at different temperatures in the range between 15 and 300 K. We achieved resistivity reduction in our samples by using an interface composition grading technique aimed at improving the VCSOA characteristics.