Influence of Silicification on the Structural and Biological Properties of Buffer‐Mediated Collagen Hydrogels

A buffer‐mediated gelation route for collagen hydrogels that allows the formation of homogeneous composite and hybrid materials with various silica sources (i.e., colloidal silica and soluble silicates) at high concentration (up to 25 × 10^?3 M ) is described. Most significant improvement in rheological properties and proliferation of primary adult human dermal fibroblasts was obtained for the silicate‐based hybrid materials. A similar trend was observed in composite materials incorporating 14 nm SiO₂ nanoparticles, although to a much lesser extent, whereas larger colloids (80 and 390 nm) did not significantly impact mechanical stability and cell behavior. Modification of 80 nm particles surface with amine groups weakens the collagen‐mineral interface, resulting in the decrease of material stability and leading to particle aggregation during the course of cell proliferation experiments.     

Study on conductivity and redox stability of iron orthovanadate

FeVO₄ was synthesised by conventional solid state technique. Impedance measurements using a silver electrode were unsuccessful due to a solid state reaction between FeVO₄ and Ag, forming α-AgVO₃ and α-Fe₂O₃ at the interface. Impedance measurements, with a platinum electrode, reaffirmed that FeVO₄ exhibits semiconductor behaviour in air. In a reducing atmosphere, 5% H₂/Ar, high electronic conductivity, from 1 S cm⁻¹ at 300 °C to 2 S cm⁻¹ at 700 °C, was observed with an activation energy of 0.13(1) eV. X-ray diffraction, thermogravimetric analysis and differential scanning calorimetry data determined that the change in electronic conductivity was due to the degradation of the material into FeV₂O₄ and α-Fe₂O₃. It is believed that the conduction was due to electron hopping between vanadium d-orbitals. Neither FeVO₄ nor FeV₂O₄ are deemed suitable as anode materials for solid oxide fuel cells, due to redox instability.     

Delivery of Nucleic Acids through the Controlled Disassembly of Multifunctional Nanocomplexes

In this study, novel pH‐responsive polyion complex micelles (PICMs) were developed for the efficient delivery of nucleic acid drugs, such as antisense oligonucleotide (AON) and short interfering RNA (siRNA). The PICMs consisted of a poly(amidoamine) (PAMAM) dendrimer–nucleic acid core and a detachable poly(ethylene glycol)‐block‐poly( propyl methacrylate‐co‐methacrylic acid) (PEG‐b‐P(PrMA‐co‐MAA)) shell. The micelles displayed a mean hydrodynamic diameter ranging from 50 to 70 nm, a narrow size distribution, and a nearly neutral surface charge. They could be lyophilized without any additives and stored in dried form. Upon redispersion in water, no change in complexation efficiency or colloidal properties was observed. Entry of the micelles into cancers cells was mediated by a monoclonal antibody fragment positioned at the extremity of the PEG segment via a disulfide linkage. Upon cellular uptake and protonation of the MAA units in the acidic endosomal environment, the micelles lost their corona, thereby exposing their positively charged endosomolytic PAMAM/nucleic acid core. When these pH‐responsive targeted PICMs were loaded with AON or siRNAs that targeted the oncoprotein Bcl‐2, they exhibited a greater transfection activity than nontargeted PICMs or commercial PAMAM dendrimers. Moreover, their nonspecific cytotoxicity was lower than that of PAMAM. The pH‐responsive PICMs reported here appear as promising carriers for the delivery of nucleic acids.     

Robust control charts for time series data

This article presents a control chart for time series data, based on the one-step-ahead forecast errors of the Holt–Winters forecasting method. We use robust techniques to prevent that outliers affect the estimation of the control limits of the chart. Moreover, robustness is important to maintain the reliability of the control chart after the occurrence of alarm observations. The properties of the new control chart are examined in a simulation study and on a real data example.     

Modification of hydrophobic/hydrophilic properties of Vulcan XC72 carbon powder by grafting of trifluoromethylphenyl and phenylsulfonic acid groups

Carbon supports (glassy carbon and Vulcan XC72 powder) were modified by electrochemical and spontaneous grafting of phenylsulfonic acid (PSA) or trifluoromethylphenyl (TFMP) groups via diazonium ion reduction. The effectiveness of the grafting was confirmed electrochemically, by XPS measurements and elemental analyses. The hydrophobic or hydrophilic character of carbon surfaces was evidenced by measuring the contact angles of drops of different liquids (water, ethylene glycol and glycerol) in heptane. The surface energy was calculated and it was found, for example, that spontaneous grafting of a glassy carbon surface by PSA groups led to an increase by a factor 20 of the surface energy compared with an unmodified glassy carbon surface. The study of the grafting of such groups on XC72 carbon powder indicated that a very low grafting ratio (in wt%) led to a significant change in the macroscopic properties of the powder. Thermogravimetric analysis coupled with mass spectroscopy measurements (TGA-MS) showed that these grafted layers were thermally stable even in the presence of dispersed platinum nanoparticles. It was shown by cyclic voltammetry that the carbon substrate modification did not affect the electrochemical behavior of platinum catalyst, since the same active surface area was determined on Pt-XC72, Pt-PSA-XC72 and Pt-TFMP-XC72 catalysts.     

Implicit Brushes for Stylized Line‐based Rendering

We introduce a new technique called Implicit Brushes to render animated 3D scenes with stylized lines in realtime with temporal coherence. An Implicit Brush is defined at a given pixel by the convolution of a brush footprint along a feature skeleton; the skeleton itself is obtained by locating surface features in the pixel neighborhood. Features are identified via image‐space fitting techniques that not only extract their location, but also their profile, which permits to distinguish between sharp and smooth features. Profile parameters are then mapped to stylistic parameters such as brush orientation, size or opacity to give rise to a wide range of line‐based styles.     

Assessment of biogas potential hazards

Biogas produced from anaerobic fermentation of organic substances represents an alternative renewable energy source. Its utilization would contribute to substantial reduction of the solid waste volume in land-filling and incineration. Biogas so produced could be utilized on site or it could be injected into the natural gas distribution network. Microbiological and chemical compositions of different biogas types were determined in order to conduct qualitative and quantitative risk assessments of the potential health hazards associated with biogas use for cooking. Biogas types that could be allowed for injection in the natural gas pipelines were listed with recommendations, while outlining the European biogas injection policy. Results indicated that the injection of the processed biogas in the distribution network did not present any additional chemical or microbiological risk to consumers when compared to natural gas, provided that the biogas resulted from the fermentation of non-dangerous waste. However, since this study did not examine the microbiological and chemical composition of biogas originating from wastewater sludges and/or industrial wastes, the injection of this type of biogas into the gas distribution network should not be allowed unless a similar risk evaluation study is conducted for each case.     

Fast and robust estimation of the multivariate errors in variables model

In the multivariate errors in variables models, one wishes to retrieve a linear relationship of the form y=β ^t x+α, where both x and y can be multivariate. The variables y and x are not directly measurable, but observed with measurement error. The classical approach to estimate the multivariate errors in variables model is based on an eigenvector analysis of the joint covariance matrix of the observations. In this paper, a projection-pursuit approach is proposed to estimate the unknown parameters. The focus is on projection indices based on half-samples. These lead to robust estimators which can be computed using fast algorithms. Fisher consistency of the procedure is shown, without the need to make distributional assumptions on the x-variables. A simulation study gives insight into the robustness and the efficiency of the procedure.     

Reasoning from last conflict(s) in constraint programming

Constraint programming is a popular paradigm to deal with combinatorial problems in artificial intelligence. Backtracking algorithms, applied to constraint networks, are commonly used but suffer from thrashing, i.e. the fact of repeatedly exploring similar subtrees during search. An extensive literature has been devoted to prevent thrashing, often classified into look-ahead (constraint propagation and search heuristics) and look-back (intelligent backtracking and learning) approaches. In this paper, we present an original look-ahead approach that allows to guide backtrack search toward sources of conflicts and, as a side effect, to obtain a behavior similar to a backjumping technique. The principle is the following: after each conflict, the last assigned variable is selected in priority, so long as the constraint network cannot be made consistent. This allows us to find, following the current partial instantiation from the leaf to the root of the search tree, the culprit decision that prevents the last variable from being assigned. This way of reasoning can easily be grafted to many variations of backtracking algorithms and represents an original mechanism to reduce thrashing. Moreover, we show that this approach can be generalized so as to collect a (small) set of incompatible variables that are together responsible for the last conflict. Experiments over a wide range of benchmarks demonstrate the effectiveness of this approach in both constraint satisfaction and automated artificial intelligence planning.     

An experimental investigation on oil mist characterization used in MQL milling process

In this study, a method is developed to determine the oil mist characteristics for the minimal quantity lubricant process. The oil mist is characterized by the size, velocity, and volume flow rate of its particles. In each case, a specific measurement process is used: the laser diffraction granulometry method, the particle image velocimetry, and the gravimetric method. These methods are used in the case of static and simple models with different inner channels. Experimental tests have been done with the same inner channel as the existing spindle inner channel. Different output models with different inner canalizations have been tested, using these experimental processes. The main goal is to control the characteristics of output oil mist as a function of the input oil mist device parameters.