Hysteretic Critical State in Coplanar Josephson Junction with Monolayer Graphene Barrier

Coplanar Al/graphene/Al junctions fabricated on the same graphene sheet deposited on silicon carbide (SiC), show robust Josephson coupling at subKelvin temperature, when the separations between the electrodes is below 400 nm. Remarkably, a hysteretic Critical State sets in when ramping an orthogonal magnetic field, with a sudden collapse of the Josephson critical current I _c when turning the field on, and a revival of I _c when inverting the sweep. Similar hysteresis can be found in granular superconducting films which may undergo the Berezinskii-Kosterlitz-Thouless transition. Here, we give quantitative arguments to prove that this odd behavior of the magnetoconductance gives evidence for an incipient Berezinskii-Kosterlitz-Thouless transition with drift and pinning of fluctuating free vortices induced by the current bias.     

The solid-state rearrangement of the Wells-Dawson K6P2W18O62·10H2O to a stable Keggin-type heteropolyanion phase: a catalyst for the selective oxidation of isobutane to isobutene

The thermal and structural stability of the Wells-Dawson-type heteropoly compound K₆P₂W₁₈O₆₂·10H₂O was examined by FT-IR spectroscopy, X-ray powder diffraction, thermogravimetric analysis and HRTEM. It was found that calcination at temperatures higher than 850 K led to the formation of a Keggin-type compound K₃PW₁₂O₄₀, containing small amounts of an additional phase originated from the high-temperature interaction between potassium phosphate (K₃PO₄ formed during the decomposition of the K₆P₂W₁₈O₆₂·10H₂O) and the Keggin-type compound itself. The Keggin-type product showed a higher activity in the selective oxidative dehydrogenation of isobutane to isobutene compared to both the Wells-Dawson precursor and to pure, authentic K₃PW₁₂O₄₀. This higher activity can be tentatively attributed to the presence of an amorphous layer of unknown stoichiometry at the surface of the thermally rearranged Wells-Dawson compound.     

Maximum Likelihood Estimation of the Cox–Ingersoll–Ross Model Using Particle Filters

This paper shows how to build in a computationally efficient way a maximum simulated likelihood procedure to estimate the Cox–Ingersoll–Ross model from multivariate time series. The advantage of this estimator is that it takes into account the exact likelihood function while avoiding the huge computational burden associated with MCMC methods and without the ad hoc assumption that certain bond yields are measured without error. The proposed methodology is implemented and tested on simulated data. For realistic parameter values the estimator seems to have good small sample properties, compared to the popular quasi maximum likelihood approach, even using moderate simulation sizes. The effect of simulation errors does not seem to undermine the estimation procedure.     

A novel composite model approach to improve software quality prediction

Context:How can quality of software systems be predicted before deployment? In attempting to answer this question, prediction models are advocated in several studies. The performance of such models drops dramatically, with very low accuracy, when they are used in new software development environments or in new circumstances.ObjectiveThe main objective of this work is to circumvent the model generalizability problem. We propose a new approach that substitutes traditional ways of building prediction models which use historical data and machine learning techniques.MethodIn this paper, existing models are decision trees built to predict module fault-proneness within the NASA Critical Mission Software. A genetic algorithm is developed to combine and adapt expertise extracted from existing models in order to derive a “composite” model that performs accurately in a given context of software development. Experimental evaluation of the approach is carried out in three different software development circumstances.ResultsThe results show that derived prediction models work more accurately not only for a particular state of a software organization but also for evolving and modified ones.ConclusionOur approach is considered suitable for software data nature and at the same time superior to model selection and data combination approaches. It is then concluded that learning from existing software models (i.e., software expertise) has two immediate advantages; circumventing model generalizability and alleviating the lack of data in software-engineering.     

Fragile base-class problem,problem?

The fragile base-class problem (FBCP) has been described in the literature as a consequence of “misusing” inheritance and composition in object-oriented programming when (re)using frameworks. Many research works have focused on preventing the FBCP by proposing alternative mechanisms for reuse, but, to the best of our knowledge, there is no previous research work studying the prevalence and impact of the FBCP in real-world software systems. The goal of our work is thus twofold: (1) assess, in different systems, the prevalence of micro-architectures, called FBCS, that could lead to two aspects of the FBCP, (2) investigate the relation between the detected occurrences and the quality of the systems in terms of change and fault proneness, and (3) assess whether there exist bugs in these systems that are related to the FBCP. We therefore perform a quantitative and a qualitative study. Quantitatively, we analyse multiple versions of seven different open-source systems that use 58 different frameworks, resulting in 301 configurations. We detect in these systems 112,263 FBCS occurrences and we analyse whether classes playing the role of sub-classes in FBCS occurrences are more change and–or fault prone than other classes. Results show that classes participating in the analysed FBCS are neither more likely to change nor more likely to have faults. Qualitatively, we conduct a survey to confirm/infirm that some bugs are related to the FBCP. The survey involves 41 participants that analyse a total of 104 bugs of three open-source systems. Results indicate that none of the analysed bugs is related to the FBCP. Thus, despite large, rigorous quantitative and qualitative studies, we must conclude that the two aspects of the FBCP that we analyse may not be as problematic in terms of change and fault-proneness as previously thought in the literature. We propose reasons why the FBCP may not be so prevalent in the analysed systems and in other systems in general.     

Calibration and validation of a solar thermal system model in Modelica

Recent advancements in the domain of modeling physical processes offer opportunities to use equation based modeling environments, such as Modelica, for the simulation of building heating, ventilation, and air-conditioning (HVAC) systems. The current work demonstrates Modelica capabilities in a case study of real building solar thermal system simulation. The simulated system is part of an innovative ENERGYbase building, designed according to the so called Passivhaus standard. Model calibration and validation procedure is developed to include optimization based parametric adjustments of component models using the monitoring data during a single week. The calibrated system adequately reproduces half a year of real system operation. Future work will concentrate on application of the developed calibration and validation methodology in the whole year overall building energy simulation.     

Selective decomposition of isopropanol using as prepared and oxidized graphite nanofibers

Three types of as prepared and treated graphite nanofibers (GNFs) were used as catalysts in the decomposition of isopropanol to propene and acetone in the presence of oxygen to evaluate the surface chemistry of the fibers. As prepared herringbone fibers were found to produce higher selectivity for propene compared to the as prepared platelet and ribbon fibers at all temperatures explored. Herringbone fibers that had undergone oxidative treatment with nitric acid, phosphoric acid, ruthenium tetroxide or potassium permanganate were also evaluated at a 290 °C. Effects of oxidation treatments on fiber structure were evaluated using a host of analytical techniques including BET, SEM/EDS, TGA, XPS, and fluorescence labeling of surface species. Selectivity for acetone dehydrogenation product or propene dehydration product could be achieved by the appropriate surface treatment. Nitric acid was the mildest treatment and the treated fibers showed minimal changes. (Potassium permanganate was a harsh treatment that almost completely degraded fiber structure, creating amorphous carbon.) Phosphoric acid treated fibers were found to produce very high conversions and almost pure selectivity for propene. Ruthenium tetroxide did not appear to have a large affect on fiber morphology; however, selectivity for acetone was much higher when GNFs were treated with ruthenium tetroxide.