The effect of Na addition on the first hydrogen absorption kinetics of cast hypoeutectic Mg–La alloys

With superior properties of Mg such as high hydrogen storage capacity (7.6 wt% H/MgH₂), low price, and low density, Mg has been widely studied as a promising candidate for solid-state hydrogen storage systems. However, a harsh activation procedure, slow hydrogenation/dehydrogenation process, and a high temperature for dehydrogenation prevent the use of Mg-based metal hydrides for practical applications. For these reasons, Mg-based alloys for hydrogen storage systems are generally alloyed with other elements to improve hydrogen sorption properties. In this article, we have added Na to cast Mg–La alloys and achieved a significant improvement in hydrogen absorption kinetics during the first activation cycle. The role of Na in Mg–La has been discussed based on the findings from microstructural observations, crystallography, and first principles calculations based on density functional theory. From our results in this study, we have found that the Na doped surface of Mg–La alloy systems have a lower adsorption energy for H₂ compared to Na-free surfaces which facilitates adsorption and dissociation of hydrogen molecules leading to improvement of absorption kinetic. The effect of Na on the microstructure of these alloys, such as eutectic refinement and a density of twins is not highly correlated with absorption kinetics.     

Moment arms and lengths of human upper limb muscles as functions of joint angles

Modeling of musculoskeletal structures requires accurate data on anatomical parameters such as muscle lengths (MLs), moment arms (MAs) and those describing the upper limb position. Using a geometrical model of planar arm movements with three degrees of freedom, we present, in an analytical form, the available information on the relationship between MAs and MLs and joint angles for thirteen human upper limb muscles. The degrees of freedom included are shoulder flexion/extension, elbow flexion/extension, and either wrist flexion/extension (the forearm in supination) or radial/ulnar deviation (the forearm in mid-pronation). Previously published MA/angle curves were approximated by polynomials. ML/angle curves were obtained by combining the constant values of MLs (defined by the distance between the origin and insertion points for a specific upper limb position) with a variable part obtained by multiplying the MA (joint radius) and the joint angle. The MAs of the prime wrist movers in radial/ulnar deviation were linear functions of the joint angle (R2 > or = 0.9954), while quadratic polynomials accurately described their MAs during wrist flexion/extensions. The relationship between MAs and the elbow angle was described by 2nd, 3rd or 5th-order polynomials (R2 > or = 0.9904), with a lesser quality of fit for the anconeus (R2 = 0.9349). In the full range of angular displacements, the length of wrist, elbow and shoulder muscles can change by 8.5, 55 and 200%, respectively.     

Responses of ligamentous fibroblasts to mechanical stimulation

Mechanical stimulation, as provided by physiotherapy or controlled motion is essentially the only factor able to improve anterior cruciate ligament (ACL) healing. We investigate the cellular effects of such stimulus. Two types of stimulations are applied on canine ACL fibroblasts: repetitive stretch of an elastomeric adhesion substrate and a laminar flow of culture media over the culture surface. Cell orientation, proliferation rate, synthesis and type of collagen as well as proteoglycans (PG) synthesis and hydrodynamic characteristics have been studied. According to our results, the fibroblasts tend to align perpendicularly to the deformation axis of their substrate, and along a laminar flow. The shear stress induced by the laminar flow does not modify significantly proliferation rate nor extracellular matrix synthesis. Substrate stretching however, increases proliferation rate, collagen synthesis, mostly type III, and PG synthesis, principally of small sizes. The characteristics of fibroblasts submitted to repeated deformation match those of fibroblasts from ligament scar tissues. Their orientation perpendicular to substratum deformation differs from the one usually encountered in the undamaged tissue: aligned on the ligament axis.     

Accelerating filtering techniques for numeric CSPs

Search algorithms for solving Numeric CSPs (Constraint Satisfaction Problems) make an extensive use of filtering techniques. In this paper¹ we show how those filtering techniques can be accelerated by discovering and exploiting some regularities during the filtering process. Two kinds of regularities are discussed, cyclic phenomena in the propagation queue and numeric regularities of the domains of the variables. We also present in this paper an attempt to unify numeric CSPs solving methods from two distinct communities, that of CSP in artificial intelligence, and that of interval analysis.     

A CP framework for testing CP

The success of several constraint-based modeling languages such as OPL, ZINC or COMET, appeals for better software engineering practices, particularly in the testing phase. This paper introduces a testing framework enabling automated test case generation for constraint programming. We propose a general framework of constraint program development which supposes that a first declarative and simple constraint model is available from the problem specifications analysis. Then, this model is refined using classical techniques such as constraint reformulation, surrogate, redundant, implied, global constraint and symmetry-breaking to form an improved constraint model that must be thoroughly tested before being used to address real-sized problems. We think that most of the faults are introduced in this refinement step and propose a process which takes the first declarative model as an oracle for detecting non-conformities and derive practical test purposes from this process. We implemented this approach in a new tool called CPTEST that was used to automatically detect non-conformities on classical benchmark programs, such as the Golomb rulers, n-queens, social golfer and the car-sequencing problems.     

Estimation of nonlinear systems via a Chebyshev approximation approach

This paper proposes to decompose the nonlinear dynamic of a chaotic system with Chebyshev polynomials to improve performances of its estimator. More widely than synchronization of chaotic systems, this algorithm is compared to other nonlinear stochastic estimator such as Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). Chebyshev polynomials orthogonality properties is used to fit a polynomial to a nonlinear function. This polynomial is then used in an Exact Polynomial Kalman Filter (ExPKF) to run real time state estimation. The ExPKF offers mean square error optimality because it can estimate exact statistics of transformed variables through the polynomial function. Analytical expressions of those statistics are derived so as to lower ExPKF algorithm computation complexity and allow real time applications. Simulations under the Additive White Gaussian Noise (AWGN) hypothesis, show relevant performances of this algorithm compared to classical nonlinear estimators.     

Evidential data mining: precise support and confidence

Associative classification has been shown to provide interesting results whenever of use to classify data. With the increasing complexity of new databases, retrieving valuable information and classifying incoming data is becoming a thriving and compelling issue. The evidential database is a new type of database that represents imprecision and uncertainty. In this respect, extracting pertinent information such as frequent patterns and association rules is of paramount importance task. In this work, we tackle the problem of pertinent information extraction from an evidential database. A new data mining approach, denoted EDMA, is introduced that extracts frequent patterns overcoming the limits of pioneering works of the literature. A new classifier based on evidential association rules is thus introduced. The obtained association rules, as well as their respective confidence values, are studied and weighted with respect to their relevance. The proposed methods are thoroughly experimented on several synthetic evidential databases and showed performance improvement.