Estimating the number of change-points in a two-dimensional segmentation model without penalization

In computational biology, numerous recent studies have been dedicated to the analysis of the chromatin structure within the cell by two-dimensional segmentation methods. Motivated by this application, we consider the problem of retrieving the diagonal blocks in a matrix of observations. The theoretical properties of the least-squares estimators of both the boundaries and the number of blocks proposed by L\'evy-Leduc et al. [2014] are investigated. More precisely, the contribution of the paper is to establish the consistency of these estimators. A surprising consequence of our results is that, contrary to the onedimensional case, a penalty is not needed for retrieving the true number of diagonal blocks. Finally, the results are illustrated on synthetic data.Comment: 30 pages, 8 figure

Interaction of CO with Surface PdZn Alloys

The adsorption and bonding configuration of CO on clean and Zn-covered Pd(111) surfaces was studied using Low Energy Electron Diffraction (LEED), Temperature Programmed Desorption (TPD) and High Resolution Electron Energy Loss Spectroscopy (HREELS). LEED and TPD results indicate that annealing at 550 K is sufficient to induce reaction between adsorbed Zn atoms and the Pd(111) surface resulting in the formation of an ordered surface PdZn alloy. Carbon monoxide was found to bond more weakly to the Zn/Pd(111) alloy surfaces compared to clean Pd(111). Zn addition was also found to alter the preferred adsorption sites for CO from threefold hollow to atop sites. Similar behavior was observed for supported Pd-Zn/Al2O3 catalysts. The results of this study show that both ensemble and electronic effects play a role in how Zn alters the interactions of CO with the surface

Stability of bimetallic Pd-Zn catalysts for the steam reforming of methanol

ZnO-supported palladium-based catalysts have been shown in recent years to be both active and selective towards the steam reforming of methanol, although they are still considered to be less active than traditional copper-based catalysts. The activity of PdZn catalysts can be significantly improved by supporting them on alumina. Here we show that the Pd/ZnO/Al2O3 catalysts have better long-term stability when compared with commercial Cu/ZnO/Al2O3 catalysts, and that they are also stable under redox cycling. The Pd/ZnO/Al2O3 catalysts can be easily regenerated by oxidation in air at 420 °C followed by re-exposure to reaction conditions at 250 °C, while the Cu/ZnO based catalysts do not recover their activity after oxidation. Reduction at high temperatures (>420 °C) leads to Zn loss from the alloy nanoparticle surface resulting in a reduced catalyst activity. However, even after such extreme treatment, the catalyst activity is regained with time on stream under reaction conditions alone, leading to highly stable catalysts. These findings illustrate that the nanoparticle surface is dynamic and changes drastically depending on the environment, and that elevated reduction temperatures are not necessary to achieve high CO2 selectivity

Evaluation of relevance of stochastic parameters on Hidden Markov Models

International audiencePrediction of physical particular phenomenon is based on knowledge of the phenomenon. This knowledge helps us to conceptualize this phenomenon around different models. Hidden Markov Models (HMM) can be used for modeling complex processes. This kind of models is used as tool for fault diagnosis systems. Nowadays, industrial robots living in stochastic environment need faults detection to prevent any breakdown. In this paper, we wish to evaluate relevance of Hidden Markov Models parameters, without a priori knowledges. After a brief introduction of Hidden Markov Model, we present the most used selection criteria of models in current literature and some methods to evaluate relevance of stochastic events resulting from Hidden Markov Models. We support our study by an example of simulated industrial process by using synthetic model of Vrignat's study (Vrignat 2010). Therefore, we evaluate output parameters of the various tested models on this process, for finally come up with the most relevant model

Homogenizing GPS Integrated Water Vapor Time Series: Benchmarking Break Detection Methods on Synthetic Data Sets

We assess the performance of different break detection methods on three sets of benchmark data sets, each consisting of 120 daily time series of integrated water vapor differences. These differences are generated from the Global Positioning System (GPS) measurements at 120 sites worldwide, and the numerical weather prediction reanalysis (ERA-Interim) integrated water vapor output, which serves as the reference series here. The benchmark includes homogeneous and inhomogeneous sections with added nonclimatic shifts (breaks) in the latter. Three different variants of the benchmark time series are produced, with increasing complexity, by adding autoregressive noise of the first order to the white noise model and the periodic behavior and consecutively by adding gaps and allowing nonclimatic trends. The purpose of this “complex experiment” is to examine the performance of break detection methods in a more realistic case when the reference series are not homogeneous. We evaluate the performance of break detection methods with skill scores, centered root mean square errors (CRMSE), and trend differences relative to the trends of the homogeneous series. We found that most methods underestimate the number of breaks and have a significant number of false detections. Despite this, the degree of CRMSE reduction is significant (roughly between 40% and 80%) in the easy to moderate experiments, with the ratio of trend bias reduction is even exceeding the 90% of the raw data error. For the complex experiment, the improvement ranges between 15% and 35% with respect to the raw data, both in terms of RMSE and trend estimations

Efficiency of flexible derotator in walking cerebral palsy children

Introduction The flexible derotator is one of the therapeutic resources used to combat primary and secondary abnormalities in walking cerebral palsy children. It was developed to reduce abnormal femoral and tibial torsions and lessen the latter's negative functional impact. Objective To determine the effect of wearing a flexible derotator on anatomic and functional parameters in walking cerebral palsy children. Methods We performed a retrospective study of walking cerebral palsy children by gathering data on bone-related parameters (femoral and tibial torsion) and functional parameters (distance and speed gait, and the energy expenditure index (EEI)). Fifteen walking cerebral palsy children were treated with the flexible derotator for one year and 15 untreated walking cerebral palsy children were included as controls. The two groups were compared in terms of the various parameters' change over time between the initial examination (the last examination prior to the start of the study or prior to use of the flexible derotator) and the final examination (after one year of follow-up). Results Right femoral anteversion and right and left external tibial torsion improved. There was a significant increase in distance and speed gait and a decrease in the EEI in walking cerebral palsy children. Conclusion Our retrospective study revealed a significant improvement in functional parameters in children with cerebral palsy, as a result of wearing the flexible derotator for at least 6 hours a day for a year. Bone parameters only improved slightly. Use of the flexible derotator could improve these children's quality of life