Intrinsic nonlinear multiscale image decomposition: A 2D empirical mode decomposition-like tool

Many works have been achieved for analyzing images with a multiscale approach. In this paper, an intrinsic and nonlinear multiscale image decomposition is proposed, based on partial differential equations (PDEs) and the image frequency contents. Our model is inspired from the 2D empirical mode decomposition (EMD) for which a theoretical study is quite nonexistent, mainly because the algorithm is based on heuristic and ad hoc elements making its mathematical study hard. This work has three main advantages. Firstly, we prove that the 2D sifting process iterations are consistent with the resolution of a nonlinear PDE, by considering continuous morphological operators to build local upper and lower envelopes of the image extrema. In addition to the fact that now differential calculus can be performed on envelopes, the introduction of such morphological filters eliminates the interpolation dependency that also terribly suffers the method. Also, contrary to former 2D empirical modes, precise mathematical definition for a class of functions are now introduced thanks to the nonlinear PDE derived from the consistency result, and their characterization on the basis of Meyer spaces. Secondly, an intrinsic multiscale image decomposition is introduced based on the image frequency contents; the proposed approach almost captures the essence and philosophy of the 2D EMD and is linked to the well known Absolutely Minimizing Lipschitz Extension model. Lastly, the proposed multiscale decomposition allows a reconstruction of images. The filterbank capability of the new multiscale decomposition algorithm is shown both on synthetic and real images, and results show that our proposed approach improves a lot on the 2D EMD. Moreover, the complexity of the proposed multiscale decomposition is very reduced compared to the 2D EMD by avoiding the surface interpolation approach, which is the core of all 2D EMD algorithms and is very time consuming. For that purpose also, our work will then be a great benefit; especially, in higher dimension spaces.     

Model-based testing of software and systems: recent advances and challenges

Model-based testing is focused on testing techniques which rely on the use of models. The diversity of systems and software to be tested implies the need for research on a variety of models and methods for test automation. We briefly review this research area and introduce several papers selected from the 22nd International Conference on Testing Software and Systems (ICTSS).     

Target Score—A Proteomics Data Selection Tool Applied to Esophageal Cancer Identifies GLUT1-Sialyl Tn Glycoforms as Biomarkers of Cancer Aggressiveness

Esophageal cancer (EC) is a life-threatening disease, demanding the discovery of new biomarkers and molecular targets for precision oncology. Aberrantly glycosylated proteins hold tremendous potential towards this objective. In the current study, a series of esophageal squamous cell carcinomas (ESCC) and EC-derived circulating tumor cells (CTCs) were screened by immunoassays for the sialyl-Tn (STn) antigen, a glycan rarely expressed in healthy tissues and widely observed in aggressive gastrointestinal cancers. An ESCC cell model was glycoengineered to express STn and characterized in relation to cell proliferation and invasion in vitro. STn was found to be widely present in ESCC (70% of tumors) and in CTCs in 20% of patients, being associated with general recurrence and reduced survival. Furthermore, STn expression in ESCC cells increased invasion in vitro, while reducing cancer cells proliferation. In parallel, an ESCC mass spectrometry-based proteomics dataset, obtained from the PRIDE database, was comprehensively interrogated for abnormally glycosylated proteins. Data integration with the Target Score, an algorithm developed in-house, pinpointed the glucose transporter type 1 (GLUT1) as a biomarker of poor prognosis. GLUT1-STn glycoproteoforms were latter identified in tumor tissues in patients facing worst prognosis. Furthermore, healthy human tissues analysis suggested that STn glycosylation provided cancer specificity to GLUT1. In conclusion, STn is a biomarker of worst prognosis in EC and GLUT1-STn glycoforms may be used to increase its specificity on the stratification and targeting of aggressive ESCC forms.     

Visceral Adipose Tissue Displays Unique Metabolomic Fingerprints in Obesity,Pre-Diabetes and Type 2 Diabetes

Visceral adipose tissue (VAT) metabolic profiling harbors the potential to disentangle molecular changes underlying obesity-related dysglycemia. In this study, the VAT exometabolome of subjects with obesity and different glycemic statuses are analyzed. The subjects (n = 19) are divided into groups according to body mass index and glycemic status: subjects with obesity and euglycemia (Ob+NGT, n = 5), subjects with obesity and pre-diabetes (Ob+Pre-T2D, n = 5), subjects with obesity and type 2 diabetes under metformin treatment (Ob+T2D, n = 5) and subjects without obesity and with euglycemia (Non-Ob, n = 4), used as controls. VATs are incubated in culture media and extracellular metabolite content is determined by proton nuclear magnetic resonance (¹H-NMR). Glucose consumption is not different between the groups. Pyruvate and pyroglutamate consumption are significantly lower in all groups of subjects with obesity compared to Non-Ob, and significantly lower in Ob+Pre-T2D as compared to Ob+NGT. In contrast, isoleucine consumption is significantly higher in all groups of subjects with obesity, particularly in Ob+Pre-T2D, compared to Non-Ob. Acetate production is also significantly lower in Ob+Pre-T2D compared to Non-Ob. In sum, the VAT metabolic fingerprint is associated with pre-diabetes and characterized by higher isoleucine consumption, accompanied by lower acetate production and pyruvate and pyroglutamate consumption. We propose that glucose metabolism follows different fates within the VAT, depending on the individuals’ health status.     

Polyethylene-layered silicate nanocomposites prepared by the polymerization-filling technique: synthesis and mechanical properties

Polyethylene-layered silicate nanocomposites were prepared by the in situ intercalative polymerization of ethylene by the so-called polymerization-filling technique and analyzed by transmission electron microscopy (TEM), X-ray diffraction analysis (XRD), differential scanning calorimetry, dynamic mechanical analysis and tensile testing. Non-modified montmorillonite and hectorite were first treated by trimethylaluminum-depleted methylaluminoxane before being contacted by a Ti-based constrained geometry catalyst. The nanocomposite was formed by addition and polymerization of ethylene. In the absence of a chain transfer agent, ultra high molecular weight polyethylene was produced. The tensile properties of these nanocomposites were poor and essentially independent of the nature and content of the silicate. Upon hydrogen addition, the molecular weight of the polyethylene was decreased with parallel improvement of the tensile and shear moduli, in relation to the filler content. The exfoliation of the layered silicates was confirmed by XRD analysis and TEM observation. The mechanical kneading of the molten nanocomposites resulted in the partial collapse of the exfoliated structure driven by the thermodynamic stability of the layered filler.     

Various Scale Levels of the Gel-to-Glass Transformation

The gel-to-glass transition in SiO₂ xerogels prepared by inorganic sol-gel synthesis was studied. The evolution of the molecular structure is traced using the infrared and lowfrequency Raman spectroscopy methods. The elastic moduli of the samples as well as the pore wall moduli at various stages of heat treatment are determined from the data on Brillouin scattering. The formation of monolithic glass on the macroscopic level manifests itself within a narrow temperature range by the dramatic increase of Young's modulus to the accepted value for fused silica. This phenomenon coincides with structural transformations on the molecular scale: (i) the definite correlation radius (the long-range order sphere) appears; (ii) local distortions of the silica network relax. The presence of structural defects influences the kinetics of vitreous SiO₂ formation during xerogel heat treatment.     

Unified reliability estimation and management of NoC based chip multiprocessors

We present a new architecture level unified reliability evaluation methodology for chip multiprocessors (CMPs). The proposed reliability estimation (REST) is based on a Monte Carlo algorithm. What distinguishes REST from the previous work is that both the computational and communication components are considered in a unified manner to compute the reliability of the CMP. We utilize REST tool to develop a new dynamic reliability management (DRM) scheme to address time-dependent dielectric breakdown and negative-bias temperature instability aging mechanisms in network-on-chip (NoC) based CMPs. Designed as a control loop, the proposed DRM scheme uses an effective neural network based reliability estimation module. The neural-network predictor is trained using the REST tool. We investigate how system’s lifetime changes when the NoC as the communication unit of the CMP is considered or not during the reliability evaluation process and find that differences can be as high as 60%. Full-system based simulations using a customized GEM5 simulator show that reliability can be improved by up to 52% using the proposed DRM scheme in a best-effort scenario with 2–9% performance penalty (using a user set target lifetime of 7 years) over the case when no DRM is employed.     

Organo-zincate molten salts as immobilising agents for organometallic catalysis

The combination of 1-n-butyl-3-methylimidazolium chloride with ZnCl₂ affords ionic mixtures with different melting point temperatures depending on the zinc molar fraction. RuCl₂(PPh₃)₃ immobilised in the low melting mixture (60°C) promotes the 1-hexene hydrogenation (turnover frequencies up to 44 min^–1) and the recovered solid catalyst phase can be reused several times.     

Influence of Plasma Instabilities in Ceramic Suspension Plasma Spraying

Direct current Suspension Plasma Spraying (SPS) allows depositing finely structured coatings. This article presents an analysis of the influence of plasma instabilities on the yttria-stabilized suspension drops fragmentation. A particular attention is paid to the treatment of suspension jet or drops according to the importance of voltage fluctuations (linked to those of the arc root) and depending on the different spray parameters such as the plasma forming gas mixture composition and mass flow rate and the suspension momentum. By observing the suspension drops injection with a fast shutter camera and a laser flash sheet triggered by a defined transient voltage level of the plasma torch, the influence of plasma fluctuations on jet or drops fragmentation is studied through the deviation and dispersion trajectories of droplets within the plasma jet. This article is an invited paper selected from presentations at the 2007 International Thermal Spray Conference and has been expanded from the original presentation. It is simultaneously published in Global Coating Solutions, Proceedings of the 2007 International Thermal Spray Conference, Beijing, China, May 14-16, 2007, Basil R. Marple, Margaret M. Hyland, Yuk-Chiu Lau, Chang-Jiu Li, Rogerio S. Lima, and Ghislain Montavon, Ed., ASM International, Materials Park, OH, 2007.     

Genetic programming for QoS-aware web service composition and selection

Web services, which can be described as functionality modules invoked over a network as part of a larger application are often used in software development. Instead of occasionally incorporating some of these services in an application, they can be thought of as fundamental building blocks that are combined in a process known as Web service composition. Manually creating compositions from a large number of candidate services is very time consuming, and developing techniques for achieving this objective in an automated manner becomes an active research field. One promising group of techniques encompasses evolutionary computing, which can effectively tackle the large search spaces characteristic of the composition problem. Therefore, this paper proposes the use of genetic programming for Web service composition, investigating three variations to ensure the creation of functionally correct solutions that are also optimised according to their quality of service. A variety of comparisons are carried out between these variations and two particle swarm optimisation approaches, with results showing that there is likely a trade-off between execution time and the quality of solutions when employing genetic programming and particle swarm optimisation. Even though genetic programming has a higher execution time for most datasets, the results indicate that it scales better than particle swarm optimisation.