Experimental control of deformability at short-term loadings in testing large-span prestressed structures

The problems in giving significance to the experimental control of deformability at short-term loadings of large-span prestressed structures in order to draw reliable conclusions on their static behaviour have been examined. With this aim the necessity of an exact evaluation of the elastic modulus of concrete together with the importance of its experimental measurement, which is too imprecise if deduced from the strength of concrete, have been pointed out. The work also shows how, by reducing uncertainty in calculating deflection, modulus measurement directly on the structure's concrete (and not only on specimens cast during construction) improves reliability in the evaluation of the static validity of the construction and the exactness of its modelling. In this regard the ultrasonic method can prove very useful. However, we have shown that it can give wrong results—especially when the load test is carried out long after the casting—if we do not make suitable corrections to take into account the evolution with time of the correlation between static and dynamic moduli, an aspect that is usually neglected.     

Acoustic detection of single particles for neutrino experiments and dark matter searches

We are developing an entirely new type of particle detector, called a silicon crystal acoustic detector (SiCAD), which senses ballistic phonons generated when an incident particle collides with a nucleus or electron in a cube of crystalline silicon. For events which deposit energy greater than about 1 keV, a 1 kg SiCAD would have spatial resolution better than 1 mm³and energy resolution better than 100 eV. We describe our laboratory research utilizing carbon thermistors, superconducting transition edge devices, and superconducting tunnel junctions as phonon sensors on the crystal faces.     

Calcium oxide and potassium hydroxide catalysed low temperature methane production from graphite and water Comparison of catalytic mechanisms

An experimental study was carried out to obtain information on the catalytic mechanisms involved in the methanation of graphite using, separately, potassium and calcium as catalysts, and water and/or hydrogen as reactants. The mechanisms for the potassium-catalysed graphite—water reaction appear to be the same in the wide temperature range from 473 to 873 K as indicated by the constant activation energy, 46 kJ mol^?1, found for methane production. The intercalation of potassium into the graphite as a possible step in the methane synthesis has been investigated and ruled out. XPS studies indicate the formation of an active form of more positively charged carbon from graphite when graphite is heated at low temperature in the presence of a calcium catalyst and water vapour. The activation energy for this carbon depolymerization reaction is 68.1 kJ mol^?1. Methane formation occurs only in the presence of hydrogen due to its reaction with the active carbon with an activation energy of 106.6 kJ mol^?1.     

Characterizing the NP-PSPACE Gap in the Satisfiability Problem for Modal Logic

There has been a great deal of work on characterizing the complexityof the satisfiability and validity problem for modal logics.In particular, Ladner showed that the satisfiability problemfor all logics between K and S4 is PSPACE-hard, while for S5it is NP-complete. We show that it is negative introspection,the axiom ¬K_p K¬K_p, that causes the gap: if we addthis axiom to any modal logic between K and S4, then the satisfiabilityproblem becomes NP-complete. Indeed, the satisfiability problemis NP-complete for any modal logic that includes the negativeintrospection axiom.     

Algorithmic aspects of Suslin's proof of Serre's conjecture

LetF be a unimodularr×s matrix with entries beingn-variate polynomials over an infinite fieldK. Denote by deg(F) the maximum of the degrees of the entries ofF and letd=1+deg(F). We describe an algorithm which computes a unimodulars×s matrixM with deg(M)=(rd) ^O(n) such thatFM=[I _r ,O], where [I _r ,O] denotes ther×s matrix obtained by adding to ther×r unit matrixI _r s–r zero columns.We present the algorithm as an arithmetic network with inputs fromK, and we count field operations and comparisons as unit cost.The sequential complexity of our algorithm amounts to field operations and comparisons inK whereas its parallel complexity isO(n ⁴ r ⁴log²(srd)).The complexity bounds and the degree bound for deg(M) mentioned above are optimal in order. Our algorithm is inspired by Suslin's proof of Serre's Conjecture.     

The inventory-routing problem with transshipment

This paper introduces the Inventory-Routing Problem with Transshipment (IRPT). This problem arises when vehicle routing and inventory decisions must be made simultaneously, which is typically the case in vendor-managed inventory systems. Heuristics and exact algorithms have already been proposed for the Inventory-Routing Problem (IRP), but these algorithms ignore the possibility of performing transshipments between customers so as to further reduce the overall cost. We present a formulation that allows transshipments, either from the supplier to customers or between customers. We also propose an adaptive large neighborhood search heuristic to solve the problem. This heuristic manipulates vehicle routes while the remaining problem of determining delivery quantities and transshipment moves is solved through a network flow algorithm. Our approach can solve four different variants of the problem: the IRP and the IRPT, under maximum level and order-up-to level policies. We perform an extensive assessment of the performance of our heuristic.     

A GMDH polynomial neural network-based method to predict approximate three-dimensional structures of polypeptides

Tertiary Protein Structure Prediction is one of the most important problems in Structural Bioinformatics. Along the last 20 years many algorithms have been proposed as to solve this problem. However, it still remains a challenging issue because of the complexity and of the dimensionality of the protein conformational search space. In this article a first principle method which uses database information for the prediction of the 3-D structure of polypeptides is presented. The technique is based on the Group Method of Data Handling (GMDH) algorithm, implemented by a software tool introduced on this work. GMDH Polynomial Neural Networks have been used with success in many fields such as data mining, knowledge discovery, pattern recognition and prediction. The proposed method was tested with seven protein sequences whose sizes vary from 14 to 54 amino acid residues. Results show that the predicted tertiary structures adopt a fold similar to the experimental structures. RMSD and secondary structure analysis reveal that the proposed method present accurate results in their predictions. The predicted structures can be used as input structures in refinement methods based on molecular mechanics (MM), e.g. molecular dynamics (MD) simulations. The search space is expected to be greatly reduced and the ab initio methods can demand a much reduced computational time to achieve a more accurate polypeptide structure.     

Viscoelastic properties of networks with low concentration of pendant chains

A good knowledge of the molecular structure of polymer networks allows to relate rheological properties with different molecular parameters. In this work we analyze the influence of low concentrations of pendant chains on the viscoelastic properties of polymer networks. Model networks, with a well defined structure, were synthesized by reacting a commercial α,ω-divinyl poly(dimethylsiloxane) (B₂) with a trifunctional cross-linker bearing silane groups (A₃) and known amounts of an anionic ω-vinyl poly(dimethylsiloxane) (B₁). The structure of the networks was predicted with a molecular model based on a mean field approach (recursive model) taking into account the initial composition of the reactants. Rheological characterization was carried out in a rotational rheometer by dynamic and stress relaxation test. Viscoelastic properties of the networks depend on both concentration and molecular weight of pendant chains. Relaxation modulus was adjusted by the empirical Chasset-Thirion equation. It was found that it provides a very good fit to the behavior of these networks prepared by end-linking. The fitting parameter m in the Chasset-Thirion equation shows a strong dependence with the molecular mass of pendant chains, but it is rhougly independent of concentration. The results agree remarkably well with the predictions of a theoretical model previously reported by our group.     

Periodic sensor switching and the random walk

Assume the random walk system is subjected to periodic sensor switching between a low-quality sensor with no delay, and a high-quality sensor with a delay. The low-quality sensor is utilized N−1$N-1$ consecutive times followed by one utilization of the high-quality sensor. A periodic Kalman filter is employed. Necessary and sufficient conditions are derived for the existence of scheduling sizes N$N$ such that the resulting periodic system has a steady state error covariance strictly smaller than both the steady state error covariances of the systems obtained with each sensor applied individually. The relationship between this result and recent developments in event driven scheduling is also provided.     

Synthesis and characterization of chitosan alkyl carbamates

The synthesis of chitosan methylcarbamate (ChMC) and ethylcarbamate (ChEC) is described by using a new methodology. Polymers with substitution degrees up to 63% for ChEC and 68.5% for ChMC were obtained. Derivatives with lower substitutions were acid soluble but those with higher ones were completely insoluble. This could be due to the loss in hydrophilic sites when the substitution degree increases. The reaction conditions and degree of substitution obtained for both derivatives were also described. A complete chemical characterization was carried out by spectroscopic techniques. The thermal degradation of chitosan and derivatives were studied in the range 25–500°C and both derivatives were shown to be thermally less stable than chitosan. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 2742–2747, 2002