The mini-conical slump flow test: Analysis and numerical study

This paper provides a general study on cement paste flow. Both mini-slump and Marsh cone tests are used to evaluate the workability of fresh paste mixtures derived from self compacting concretes. A numerical approach is used to reproduce global flow behavior and to check the accuracy of the obtained viscosity as well as the validity of expressions available in the literature giving yield stress from the final diameter of slumped paste. The computational modeling allows access to local information in order to analyze different regions and corresponding flow types, i.e. falling solid and flowing fresh cementing material mixtures.The limitation of some empirical models allowing the prediction of yield stress τ₀ and plastic viscosity μ from mini-slump tests is underlined, conditions of validity are expressed and a new expression is proposed.     

Biosynthesis of the Myxobacterial Antibiotic Corallopyronin A

Corallopyronin A is a myxobacterial compound with potent antibacterial activity. Feeding experiments with labelled precursors resulted in the deduction of all biosynthetic building blocks for corallopyronin A and revealed an unusual feature of this metabolite: its biosynthesis from two chains, one solely PKS‐derived and the other NRPS/PKS‐derived. The starter molecule is believed to be carbonic acid or its monomethyl ester. The putative corallopyronin A biosynthetic gene cluster is a trans‐AT‐type mixed PKS/NRPS gene cluster, containing a β‐branching cassette. Striking features of this gene cluster are a NRPS‐like adenylation domain that is part of a PKS‐type module and is believed to be responsible for glycine incorporation, as well as split modules with individual domains occurring on different genes. It is suggested that CorB is a trans‐acting ketosynthase and it is proposed that it catalyses the Claisen condensation responsible for the interconnection of the two chains. Additionally, the stereochemistry of corallopyronin A was deduced by a combination of a modified Mosher's method and ozonolysis with subsequent chiral GC analyses.     

Sensory profiles and preference analysis in ornamental horticulture: The case of the rosebush

The context of ornamental horticulture is considered in order to extend the techniques of sensory and preference evaluation by taking the rosebush as a plant model. In a preliminary study (Boumaza, Demotes-Mainard, Huché-Thélier, & Guérin, 2009), a sensory evaluation was conducted in order to set up a list of attributes. Subsequently, this list was adapted to assess 10 rosebushes. After the control of the panel performance using a multivariate strategy of analysis, the average scores were used in product mapping. The evaluation of the preferences with regard to these rosebushes was undertaken: 253 subjects were asked to rank the products by decreasing order of liking. Thereafter, the preference data were subjected to an internal preference mapping and a cluster analysis. Six homogeneous segments of consumers were eventually retained. By way of performing an external preference mapping, the average ranks were regressed upon the sensory attributes using principal component regression: the preferences of 67% of the consumers were satisfactorily explained by the attributes.     

EM323: a line search based algorithm for solving high-dimensional continuous non-linear optimization problems

This paper presents a performance study of a one-dimensional search algorithm for solving general high-dimensional optimization problems. The proposed approach is a hybrid between a line search algorithm of Glover (The 3-2-3, stratified split and nested interval line search algorithms. Research report, OptTek Systems, Boulder, CO, 2010) and an improved variant of a global method of Gardeux et al. (Unidimensional search for solving continuous high-dimensional optimization problems. In: ISDA ’09: Proceedings of the 2009 ninth international conference on intelligent systems design and applications, IEEE Computer Society, Washington, DC, USA, pp 1096–1101, 2009) that uses line search algorithms as subroutines. The resulting algorithm, called EM323, was tested on 19 scalable benchmark functions, with a view to observing how optimization techniques for continuous optimization problems respond with increasing dimension. To this end, we report the algorithm’s performance on the 50, 100, 200, 500 and 1,000-dimension versions of each function. Computational results are given comparing our method with three leading evolutionary algorithms. Statistical analysis discloses that our method outperforms the other methods by a significant margin.     

Regularization, Scale-Space, and Edge Detection Filters

Computational vision often needs to deal with derivatives ofdigital images. Such derivatives are not intrinsic properties ofdigital data; a paradigm is required to make them well-defined.Normally, a linear filtering is applied. This can be formulated interms of scale-space, functional minimization, or edge detectionfilters. The main emphasis of this paper is to connect these theoriesin order to gain insight in their similarities and differences. We donot want, in this paper, to take part in any discussion of how edgedetection must be performed, but will only link some of the current theories. We take regularization (or functional minimization) as astarting point, and show that it boils down to Gaussian scale-space ifwe require scale invariance and a semi-group constraint to besatisfied. This regularization implies the minimization of afunctional containing terms up to infinite order of differentiation.If the functional is truncated at second order, the Canny-Deriche filter arises. It is also shown that higher dimensional regularizationboils down to a rotated version of the one dimensional case, whenCartesian invariance is imposed and the image is vanishing at theborders. This means that the results from 1D regularization can beeasily generalized to higher dimensions. Finally we show how anefficient implementation of regularization of order n can be made byrecursive filtering using 2n multiplications and additions peroutput element without introducing any approximation.     

The blue bronze Tl0.30MoO3 structure and physical properties

Crystals of the so-called blue bronze Tl_0.30MoO₃ were prepared by tempering molten mixtures. The structure was refined in the space group C2/m from 2171 reflections corrected for absorption. The R and R_w factors obtained from the last refinement cycle are 0.030 and 0.036 respectively for 114 refined parameters. The Zachariasen method enabled the 4d distribution over the three independent sites Mo1, Mo2 and Mo3 to be determined and gave 16.6 %, 39.7 % and 43.7 % respectively.For each octahedron a close correlation appears between the number of shared edges, the formal molybdenum charge and its eccentricity within the polyhedron. It is found that the molybdenum Mo1 has the highest formal charge ; this site does not seem to participate in the electrical conductivity which takes place mainly in the slabs thanks to the molybdenum sites Mo2 and Mo3 which represent 83.4 % of the electron density.Tl_0.30MoO₃ shows a metal-to-semiconductor transition at 185 K, probably of Peierls type. We propose that the non-linear effects and metastability phenomena observed below 180 K, in the non-ohmic regime are very likely due to the depinning of a charge density wave, as it has been found in the blue bronze K_0.30MoO₃     

Sensitive magnetic field sensor using 2D magnetic photonic crystal slab waveguide based on BIG/GGG structure

A kind of magnetic field sensor (MFS) using a two-dimensional (2D) magnetic photonic crystal (MPC) slab waveguide as the sensing structure is proposed and investigated numerically. The slab structure is based on bismuth iron garnet (BIG), a well-known magnetic material with effective magnetooptical (MO) properties, sandwiched with gadolinium gallium garnet (GGG) as substrate. The complete photonic bandgap (PBG) of the 2D MPC is simulated and optimized for realization of polarization-independent waveguides. The simulation results show that the width and position of the complete PBG depend on the thickness of the BIG slab and the radius of the air holes used in the design. By reducing the lightwave propagation losses and enhancing the mode conversion ratio, increased sensitivity is obtained. Based on the Faraday effect, a good linear relationship is observed between the normalized output light intensity and the magnetic field strength as the gyrotropy parameter g is varied from 0.13 to 0.19, a g-range used as the sensor dynamic range. The remarkable enhancement in sensing performance due to the MO effect makes the designed device suitable for magnetic field sensing. The results are discussed to provide a basis for investigation of 2D MPC slab waveguides based on the same structure, which are of particular interest for development of highly sensitive MFSs.     

Nanobodies and Nanocrystals: Highly Sensitive Quantum Dot‐Based Homogeneous FRET Immunoassay for Serum‐Based EGFR Detection

Semiconductor quantum dot nanocrystals (QDs) for optical biosensing applications often contain thick polyethylene glycol (PEG)‐based coatings in order to retain the advantageous QD properties in biological media such as blood, serum or plasma. On the other hand, the application of QDs in Förster resonance energy transfer (FRET) immunoassays, one of the most sensitive and most common fluorescence‐based techniques for non‐competitive homogeneous biomarker diagnostics, is limited by such thick coatings due to the increased donor‐acceptor distance. In particular, the combination with large IgG antibodies usually leads to distances well beyond the common FRET range of approximately 1 to 10 nm. Herein, time‐gated detection of Tb‐to‐QD FRET for background suppression and an increased FRET range is combined with single domain antibodies (or nanobodies) for a reduced distance in order to realize highly sensitive QD‐based FRET immunoassays. The “(nano)²” immunoassay (combination of nanocrystals and nanobodies) is performed on a commercial clinical fluorescence plate reader and provides sub‐nanomolar (few ng/mL) detection limits of soluble epidermal growth factor receptor (EGFR) in 50 μL buffer or serum samples. Apart from the first demonstration of using nanobodies for FRET‐based immunoassays, the extremely low and clinically relevant detection limits of EGFR demonstrate the direct applicability of the (nano)^2‐ assay to fast and sensitive biomarker detection in clinical diagnostics.     

Experimental study and modelling of tool temperature distribution in orthogonal cutting of AISI 316L and AISI 3115 steels

Cutting tool temperature distribution was mapped using the IR-CCD technique during machining of carbon steel AISI 3115 and stainless steel AISI 316L under orthogonal cutting conditions using flat-face geometry inserts. The effect of work material treatment on tool temperature was investigated, and the results showed that AISI 3115 in heat-treated state displayed higher tool temperature than the as-rolled state. Stainless steel 316L with high sulphur content (0.027?wt.%) and calcium treatment displayed lower cutting tool temperature than the variant with low sulphur (0.009?wt.%). The experimental results were compared with theoretical tool temperature distributions based on a modified version of Komanduri and Hou??s analytical model. In particular, variable frictional heat source and secondary shear were introduced and modelling of the tool stress distribution on rake surface was also considered.