Model-to-Code transformation from product-line architecture models to aspectJ

Software Product Line Engineering has significant advantages in family-based software development. The common and variable structure for all products of a family is defined through a Product-Line Architecture (PLA) that consists of a common set of reusable components and connectors which can be configured to build the different products. The design of PLA requires solutions for capturing such configuration (variability). The Flexible-PLA Model is a solution that supports the specification of external variability of the PLA configuration, as well as internal variability of components. However, a complete support for product-line development requires translating architecture specifications into code. This complex task needs automation to avoid human error. Since Model-Driven Development allows automatic code generation from models, this paper presents a solution to automatically generate AspectJ code from Flexible-PLA models previously configured to derive specific products. This solution is supported by a modeling framework and validated in a software factory.

Model Based On-Line Energy Prediction System for Semi-Autonomous Mobile Robots

Maximizing energy autonomy is a consistent challenge when deploying mobile robots in ionizing radiation or other hazardous environments. Having a reliable robot system is essential for successful execution of missions and to avoid manual recovery of the robots in environments that are harmful to human beings. For deployment of robots missions at short notice, the ability to know beforehand the energy required for performing the task is essential. This paper presents a on-line method for predicting energy requirements based on the pre-determined power models for a mobile robot. A small mobile robot, Khepera III is used for the experimental study and the results are promising with high prediction accuracy. The applications of the energy prediction models in energy optimization and simulations are also discussed along with examples of significant energy savings.

A discrete spectral model for intermediate crack debonding in FRP-strengthened RC beams

One of the common failure modes of reinforced concrete (RC) beams strengthened in flexure with a bonded fibre-reinforced polymer (FRP) is intermediate crack (IC) debonding, which is originated at a critical section in the vicinity of flexural cracks and propagates to a plate end. Despite considerable research over the last years, few reliable and simplified IC debonding strength models have been developed. This paper firstly presents a one-dimensional model based on the discrete crack approach for concrete and the spectral element method for the numerical simulation of the IC debonding process. The progressive formation of flexural cracks and subsequent concrete-FRP interfacial debonding is formulated by the introduction of a new element able to represent both phenomena simultaneously without perturbing the numerical procedure. Furthermore, with the proposed model, high frequency dynamic response for these kinds of structures can also be obtained in a very simple and non-expensive way, which makes this procedure very useful as a tool for diagnoses and detection of debonding in its initial stage by monitoring the change in local dynamic characteristics.

Debonding detection of FRP strengthened concrete beams by using impedance measurements and an ensemble PSO adaptive spectral model

An impedance-based midspan debonding identification method for RC beams strengthened with FRP strips is presented in this paper using piezoelectric ceramic (PZT) sensor?actuators. To reach this purpose, firstly, a two-dimensional electromechanical impedance model is proposed to predict the electrical admittance of the PZT transducer bonded to the FRP strips of an RC beam. Considering the impedance is measured in high frequencies, a spectral element model of the bonded-PZT?FRP strengthened beam is developed. This model, in conjunction with experimental measurements of PZT transducers, is used to present an updating methodology to quantitatively detect interfacial debonding of these kinds of structures. To improve the performance and accuracy of the detection algorithm in a challenging problem such as ours, the structural health monitoring approach is solved with an ensemble process based on particle of swarm. An adaptive mesh scheme has also been developed to increase the reliability in locating the area in which debonding initiates. Predictions carried out with experimental results have showed the effectiveness and potential of the proposed method to detect prematurely at its earliest stages a critical failure mode such as that due to midspan debonding of the FRP strip.

Measurement of plasma electron density generated in an experiment of laser shock processing, utilizing the H­α­-line

In this work we have realized plasma diagnosis produced by Laser (LPP), by means of emission spectroscopy in a Laser Shock Processing (LSP). The LSP has been proposed as an alternative technology, competitive with classical surface treatments. The ionic species present in the plasma together with electron density and its temperature provide significant indicators of the degree of surface effect of the treated material. In order to analyze these indicators, we have realized spectroscopic studies of optical emission in the laser-generated plasmas in different situations. We have worked focusing on an aluminum sample (Al2024) in air and/or in LSP conditions (water flow) a Q-switched laser of Nd:YAG (λ = 1.06 μm, 10 ns of pulse duration, running at 10 Hz repetition rate). The pulse energy was set at 2,5 J per pulse. The electron density has been measured using, in every case, the Stark broadening of H Balmer α line (656.27 nm). In the case of the air, this measure has been contrasted with the value obtained with the line of 281.62 nm of Al II. Special attention has been paid to the self-absorption of the spectral lines used. The measures were realized with different delay times after the pulse of the laser (1–8 μs) and with a time window of 1 μs. In LSP the electron density obtained was between 1017 cm−3 for the shortest delays (4–6 μs), and 1016 cm−3 for the greatest delays (7,8 μs).

Intrastriatal injection of an adenoviral vector expressing glial-cell-line-derived neurotrophic factor prevents dopaminergic neuron degeneration and behavioral impairment in a rat model of Parkinson disease

Glial-cell-line-derived neurotrophic factor (GDNF) is a potent neurotrophic factor for adult nigral dopamine neurons in vivo. GDNF has both protective and restorative effects on the nigro-striatal dopaminergic (DA) system in animal models of Parkinson disease. Appropriate administration of this factor is essential for the success of its clinical application. Since it cannot cross the blood–brain barrier, a gene transfer method may be appropriate for delivery of the trophic factor to DA cells. We have constructed a recombinant adenovirus (Ad) encoding GDNF and injected it into rat striatum to make use of its ability to infect neurons and to be retrogradely transported by DA neurons. Ad-GDNF was found to drive production of large amounts of GDNF, as quantified by ELISA. The GDNF produced after gene transfer was biologically active: it increased the survival and differentiation of DA neurons in vitro. To test the efficacy of the Ad-mediated GDNF gene transfer in vivo, we used a progressive lesion model of Parkinson disease. Rats received injections unilaterally into their striatum first of Ad and then 6 days later of 6-hydroxydopamine. We found that mesencephalic nigral dopamine neurons of animals treated with the Ad-GDNF were protected, whereas those of animals treated with the Ad-β-galactosidase were not. This protection was associated with a difference in motor function: amphetamine-induced turning was much lower in animals that received the Ad-GDNF than in the animals that received Ad-β-galactosidase. This finding may have implications for the development of a treatment for Parkinson disease based on the use of neurotrophic factors.

Midbrain injection of recombinant adeno-associated virus encoding rat glial cell line-derived neurotrophic factor protects nigral neurons in a progressive 6-hydroxydopamine-induced degeneration model of Parkinson’s disease in rats

A recombinant adeno-associated virus (rAAV) vector capable of infecting cells and expressing rat glial cell line-derived neurotrophic factor (rGDNF), a putative central nervous system dopaminergic survival factor, under the control of a potent cytomegalovirus (CMV) immediate/early promoter (AAV-MD-rGDNF) was constructed. Two experiments were performed to evaluate the time course of expression of rAAV-mediated GDNF protein expression and to test the vector in an animal model of Parkinson’s disease. To evaluate the ability of rAAV-rGDNF to protect nigral dopaminergic neurons in the progressive Sauer and Oertel 6-hydroxydopamine (6-OHDA) lesion model, rats received perinigral injections of either rAAV-rGDNF virus or rAAV-lacZ control virus 3 weeks prior to a striatal 6-OHDA lesion and were sacrificed 4 weeks after 6-OHDA. Cell counts of back-labeled fluorogold-positive neurons in the substantia nigra revealed that rAAV-MD-rGDNF protected a significant number of cells when compared with cell counts of rAAV-CMV-lacZ-injected rats (94% vs. 51%, respectively). In close agreement, 85% of tyrosine hydroxylase-positive cells remained in the nigral rAAV-MD-rGDNF group vs. only 49% in the lacZ group. A separate group of rats were given identical perinigral virus injections and were sacrificed at 3 and 10 weeks after surgery. Nigral GDNF protein expression remained relatively stable over the 10 weeks investigated. These data indicate that the use of rAAV, a noncytopathic viral vector, can promote delivery of functional levels of GDNF in a degenerative model of Parkinson’s disease.

A user's guide to a steady-state shallow-water directional spectral wave model /

Includes abstract.

A user's guide to the N-line model : a numerical model to simulate sediment transport in the vicinity of coastal structures /

"August 1987."

CALINE2 - an improved microscale model for the dispersion of air pollutants from a line source. Interim report.

Federal Highway Administration, Washington, D.C.

Critical behavior of one-particle spectral weights in the transverse Ising model

We investigate the critical behavior of the spectral weight of a single quasiparticle, one of the key observables in experiment, for the particular case of the transverse Ising model. Series expansions are calculated for the linear chain and the square and simple cubic lattices. For the chain model, a conjectured exact result is discovered. For the square and simple cubic lattices, series analyses are used to estimate the critical exponents. The results agree with the general predictions of Sachdev [Quantum Phase Transitions (Cambridge University Press, Cambridge, England, 1999)].

A mathematical model for assembly line balancing model to consider disordering sequence of workstations

Purpose – A binary integer programming model for the simple assembly line balancing problem (SALBP), which is well known as SALBP-1, was formulated more than 30 years ago. Since then, a number of researchers have extended the model for the variants of assembly line balancing problem.The model is still prevalent nowadays mainly because of the lower and upper bounds on task assignment. These properties avoid significant increase of decision variables. The purpose of this paper is to use an example to show that the model may lead to a confusing solution. Design/methodology/approach – The paper provides a remedial constraint set for the model to rectify the disordered sequence problem. Findings – The paper presents proof that the assembly line balancing model formulated by Patterson and Albracht may lead to a confusing solution. Originality/value – No one previously has found that the commonly used model is incorrect.