Model-driven engineering for mobile robotic systems: a systematic mapping study

Software and Systems Modeling - Mobile robots operate in various environments (e.g. aquatic, aerial, or terrestrial), they come in many diverse shapes and they are increasingly becoming parts of...     

2-Phenyloxazole-4-carboxamide as a Scaffold for Selective Inhibition of Human Monoamine Oxidase B

A series of 2-phenyloxazoles bearing an amide group at position 4 were designed and synthesized for evaluation as potential inhibitors of human recombinant monoamine oxidases (hrMAOs). Results of kinetics experiments demonstrated that all compounds behave as competitive MAO inhibitors, with good selectivity toward the MAO-B isoform. The most potent and selective derivatives are characterized by inhibition constant (K_i) values in the sub-micromolar range and a good selectivity index (K_{i MAO-A}/K_{i MAO-B}>50). Some derivatives were also found to be able to inhibit MAO activity in nerve growth factor (NGF)-differentiated PC12 cells, taken as a model of neuronal cells. In particular, 2-(2-hydroxyphenyl)-N-phenyloxazole-4-carboxamide (compound 4 a ) may be a promising new scaffold, exerting the highest selectivity and inhibitory effect toward MAOs in NGF-differentiated PC12 cell lysates, without compromising cell viability. Molecular docking analysis allowed a rationalization of the experimentally observed binding affinity and selectivity.     

DeMIMA: A Multilayered Approach for Design Pattern Identification

Design patterns are important in object-oriented programming because they offer design motifs, elegant solutions to recurrent design problems, which improve the quality of software systems. Design motifs facilitate system maintenance by helping to understand design and implementation. However, after implementation, design motifs are spread throughout the source code and are thus not directly available to maintainers. We present DeMIMA, an approach to identify semi-automatically micro-architectures that are similar to design motifs in source code and to ensure the traceability of these micro-architectures between implementation and design. DeMIMA consists of three layers: two layers to recover an abstract model of the source code, including binary class relationships, and a third layer to identify design patterns in the abstract model. We apply DeMIMA to five open-source systems and, on average, we observe 34% precision for the considered 12 design motifs. Through the use of explanation-based constraint programming, DeMIMA ensures 100% recall on the five systems. We also apply DeMIMA on 33 industrial components.     

Plasma mevalonate concentrations in uremic patients

Mevalonic acid (mevalonate or MVA), is an obligate precursor in the biosynthetic pathway of cholesterol. It is partially metabolized by the kidneys and its plasma concentrations are an index of endogenous cholesterol synthesis. The aim of the present study was to evaluate plasma MVA concentrations in uremic patients with different degrees of chronic renal failure (CRF; group A), and the effects of a single hemodialysis treatment on plasma MVA in a group of patients with end-stage renal disease (ESRD; group B). CRF patients exhibited a higher mean basal mevalonate concentration (13.3 +/- 6.5 ng/ml) than control subjects (4.68 +/- 1.32 ng/ml; P < 0.001). A statistically significant direct correlation was evident in CRF patients between mevalonate and creatinine plasma levels (r = 0.86; P < 0.001). A single hemodialysis treatment was associated with a significant reduction of plasma mevalonate concentrations four hours after the hemodialysis session (-57%; P < 0.001) and an increase up to the basal values 24 hours after the end of the treatment. In conclusion, our results demonstrated: (i) higher plasma MVA concentrations in patients with decreased renal function; (ii) a direct relationship between plasma MVA levels and the degree of kidney failure as expressed by creatinine plasma concentrations; and (iii) a clear cut reduction of elevated plasma MVA levels after a single hemodialysis treatment.     

On the cramer-rao bound for carrier frequency estimation in the presence of phase noise

We consider the carrier frequency offset estimation in a digital burst-mode satellite transmission affected by phase noise. The corresponding Cramer-Rao lower bound is analyzed for linear modulations under a Wiener phase noise model and in the hypothesis of knowledge of the transmitted data. Even if we resort to a Monte Carlo average, from a computational point of view the evaluation of the Cramer-Rao bound is very hard. We introduce a simple but very accurate approximation that allows to carry out this task in a very easy way. As it will be shown, the presence of the phase noise produces a remarkable performance degradation of. the frequency estimation accuracy. In addition, we provide asymptotic expressions of the Cramer-Rao bound, from which the effect of the phase noise and the dependence on the system parameters of the frequency offset estimation accuracy clearly result. Finally, as a by-product of our derivations and approximations, we derive a couple of estimators specifically tailored for the phase noise channel that will be compared with the classical Rife and Boorstyn algorithm, gaining in this way some important hints on the estimators to be used in this scenario     

Comparison and Evaluation of Clone Detection Tools

Many techniques for detecting duplicated source code (software clones) have been proposed in the past. However, it is not yet clear how these techniques compare in terms of recall and precision as well as space and time requirements. This paper presents an experiment that evaluates six clone detectors based on eight large C and Java programs (altogether almost 850 KLOC). Their clone candidates were evaluated by one of the authors as an independent third party. The selected techniques cover the whole spectrum of the state-of-the-art in clone detection. The techniques work on text, lexical and syntactic information, software metrics, and program dependency graphs.     

An exploratory study of the impact of antipatterns on class change- and fault-proneness

Antipatterns are poor design choices that are conjectured to make object-oriented systems harder to maintain. We investigate the impact of antipatterns on classes in object-oriented systems by studying the relation between the presence of antipatterns and the change- and fault-proneness of the classes. We detect 13 antipatterns in 54 releases of ArgoUML, Eclipse, Mylyn, and Rhino, and analyse (1) to what extent classes participating in antipatterns have higher odds to change or to be subject to fault-fixing than other classes, (2) to what extent these odds (if higher) are due to the sizes of the classes or to the presence of antipatterns, and (3) what kinds of changes affect classes participating in antipatterns. We show that, in almost all releases of the four systems, classes participating in antipatterns are more change-and fault-prone than others. We also show that size alone cannot explain the higher odds of classes with antipatterns to underwent a (fault-fixing) change than other classes. Finally, we show that structural changes affect more classes with antipatterns than others. We provide qualitative explanations of the increase of change- and fault-proneness in classes participating in antipatterns using release notes and bug reports. The obtained results justify a posteriori previous work on the specification and detection of antipatterns and could help to better focus quality assurance and testing activities.