Optical and electrical characterization of carbon nanoparticles produced in laminar premixed flames

Optical and electrical properties of carbonaceous particles produced in laboratory scale, premixed ethylene/air flames are obtained. Light absorption and Raman spectroscopy show that the change in particle nanostructure follows a graphitization trajectory as the flame richness increases. The optical band gap decreases and the size of the aromatic network in the particle increases, while the interlayer spacing between parallel layers decreases. The electrical conductivity of the materials increases by increasing flame richness in agreement to the graphitization trajectory. A non-ohmic behavior has been found and explained in terms of electron tunneling in a percolative network. Our results show that the electrical properties of flame formed carbon nanoparticles are strongly dependent on their nanostructure, and hence they have to be used carefully for the determination of particle concentration with conductometric sensors. Moreover, the dependence of the electrical properties of combustion formed particles might be useful for the development of cheap sensors for the selective detection of different classes of combustion aerosols.     

Surface-initiated atom transfer radical polymerization of polyhedral oligomeric silsesquioxane (POSS) methacrylate from flat silicon wafer

A polyhedral oligomeric silsesquioxane (POSS) methacrylate monomer, i.e. 3-(3,5,7,9,11,13,15-heptacyclopentyl-pentacyclo [9.5.1.1.^3,91.^5,151^7,13]-octasiloxane-1-yl) propyl methacrylate (POSS-MA), was directly grafted from flat silicon wafers using surface-initiated atom transfer radical polymerization (ATRP). Two methods were used to improve the system livingness and control of polymer molecular weights. By ‘adding free initiator’ method, a linear relationship between the grafted poly(POSS-MA) layer thickness and monomer conversion was observed. By ‘adding deactivator’ method, the poly(POSS-MA) thickness increased linearly with reaction time. Poly(POSS-MA) layers up to 40 nm were obtained. The chemical compositions measured by X-ray photoelectron spectroscopy (XPS) agreed well with their theoretical values. Water contact angle measurements revealed that the grafted poly(POSS-MA) was extremely hydrophobic. The surface morphologies of the grafted polymer layers were studied by an atom force microscopy (AFM).     

Effect of water vapour partial pressure on the chromia (Cr2O3)-based scale stability

The kinetics of the Cr₂O₃-based scale oxidation and volatilisation were studied in the presence of water vapour (H₂O). A commercial Cr₂O₃-based scale forming Type 310S stainless steel was examined at the ambient pressure (0.1?MPa) and 550°C in relatively low and high H₂O-containing environments of air-10% H₂O and air-70% H₂O, respectively. The increase in the partial pressure of H₂O (p_H2O) from 10 to 70% resulted in the transition of the oxidation and volatilisation kinetics from the parabolic rate law in air-10% H₂O to the paralinear rate law in air-70% H₂O. The kinetics transition was attributed to the increase in the Cr loss rate from the base scale after coupons exposure in air-70% H₂O. The significant role of Mn alloying element in the base scale protectiveness was also discussed in the context of the Cr₂O₃-based scale stability.     

AXL Receptor in Breast Cancer: Molecular Involvement and Therapeutic Limitations

Breast cancer was one of the first malignancies to benefit from targeted therapy, i.e., treatments directed against specific markers. Inhibitors against HER2 are a significant example and they improved the life expectancy of a large cohort of patients. Research on new biomarkers, therefore, is always current and important. AXL, a member of the TYRO-3, AXL and MER (TAM) subfamily, is, today, considered a predictive and prognostic biomarker in many tumor contexts, primarily breast cancer. Its oncogenic implications make it an ideal target for the development of new pharmacological agents; moreover, its recent role as immune-modulator makes AXL particularly attractive to researchers involved in the study of interactions between cancer and the tumor microenvironment (TME). All these peculiarities characterize AXL as compared to other members of the TAM family. In this review, we will illustrate the biological role played by AXL in breast tumor cells, highlighting its molecular and biological features, its involvement in tumor progression and its implication as a target in ongoing clinical trials.     

Kuwanon‐L as a New Allosteric HIV‐1 Integrase Inhibitor: Molecular Modeling and Biological Evaluation

HIV‐1 integrase (IN) active site inhibitors are the latest class of drugs approved for HIV treatment. The selection of IN strand‐transfer drug‐resistant HIV strains in patients supports the development of new agents that are active as allosteric IN inhibitors. Here, a docking‐based virtual screening has been applied to a small library of natural ligands to identify new allosteric IN inhibitors that target the sucrose binding pocket. From theoretical studies, kuwanon‐L emerged as the most promising binder and was thus selected for biological studies. Biochemical studies showed that kuwanon‐L is able to inhibit the HIV‐1 IN catalytic activity in the absence and in the presence of LEDGF/p75 protein, the IN dimerization, and the IN/LEDGF binding. Kuwanon‐L also inhibited HIV‐1 replication in cell cultures. Overall, docking and biochemical results suggest that kuwanon‐L binds to an allosteric binding pocket and can be considered an attractive lead for the development of new allosteric IN antiviral agents.     

An adaptive flocking algorithm for performing approximate clustering

This paper presents an approach based on an adaptive bio-inspired method to make state of the art clustering algorithms scalable and to provide them with an any-time behavior. The method is based on the biology-inspired paradigm of a flock of birds, i.e. a population of simple agents interacting locally with each other and with the environment. The flocking algorithm provides a model of decentralized adaptive organization useful to solve complex optimization, classification and distributed control problems. This approach avoids the sequential search of canonical clustering algorithms and permits a scalable implementation.The method is applied to design two novel clustering algorithms based on the main principles of two popular clustering algorithms: DBSCAN and SNN. This apporach can identify clusters of widely varying shapes and densities and is able to extract an approximate view of the clusters whenever it is required. Both the algorithms have been evaluated on synthetic and real world data sets and the impact of the flocking strategy on performance has been evaluated.     

Fast algorithms for nonparametric population modeling of large data sets

Population models are widely applied in biomedical data analysis since they characterize both the average and individual responses of a population of subjects. In the absence of a reliable mechanistic model, one can resort to the Bayesian nonparametric approach that models the individual curves as Gaussian processes. This paper develops an efficient computational scheme for estimating the average and individual curves from large data sets collected in standardized experiments, i.e. with a fixed sampling schedule. It is shown that the overall scheme exhibits a “client-server” architecture. The server is in charge of handling and processing the collective data base of past experiments. The clients ask the server for the information needed to reconstruct the individual curve in a single new experiment. This architecture allows the clients to take advantage of the overall data set without violating possible privacy and confidentiality constraints and with negligible computational effort.     

On the power of structural decompositions of graph-based representations of constraint problems

The Constraint Satisfaction Problem (CSP) is a central issue of research in Artificial Intelligence. Due to its intractability, many efforts have been made in order to identify tractable classes of CSP instances, and in fact deep and useful results have already been achieved. In particular, this paper focuses on structural decomposition methods, which are essentially meant to look for near-acyclicity properties of the graphs or hypergraphs that encode the structure of the constraints interactions. In general, constraint scopes comprise an arbitrary number of variables, and thus this structure may be naturally encoded via hypergraphs. However, in many practical applications, decomposition methods are applied over suitable graph representations of the (possibly non-binary) CSP instances at hand. Despite the great interest in such binary approaches, a formal analysis of their power, in terms of their ability of identifying islands of tractability, was missing in the literature.The aim of this paper is precisely to fill this gap, by studying the relationships among binary structural methods, and by providing a clear picture of the tractable fragments of CSP that can be specified with respect to each of these decomposition approaches, when they are applied to binary representations of non-binary CSP instances. In particular, various long-standing questions about primal, dual and incidence graph encodings are answered. The picture is then completed by comparing methods on binary encodings with methods specifically conceived for non-binary constraints.     

A Mathematical Approach in the Design of Arterial Bypass Using Unsteady Stokes Equations

In this paper we present an approach for the study of Aorto-Coronaric bypass anastomoses configurations using unsteady Stokes equations. The theory of optimal control based on adjoint formulation is applied in order to optimize the shape of the zone of the incoming branch of the bypass (the toe) into the coronary according to several optimality criteria.Dedicated to David Gottlieb on the occasion of his 60th birthdayValery Agoshkov: This work has been prepared when the first author was a visiting professor at Institut d’Analyse et Calcul Scientifique of the école Polytechnique Fédérale de Lausanne