Agronomic performance of high oleic,low linolenic soybean in Tennessee

Soybean oil hydrogenation alters the linolenic acid molecule to prevent the oil from becoming rancid, however, health reports have indicated trans-fat caused by hydrogenation, is not generally regarded as safe. Typical soybeans contain approximately 80 g kg⁻¹ to 120 g kg⁻¹ linolenic acid and 240 g kg⁻¹ of oleic acid. In an effort to accommodate the need for high-quality oil, the United Soybean Board introduced an industry standard for a high oleic acid greater than 750 g kg⁻¹ and linolenic acid less than 30 g kg⁻¹ oil. By combing mutations in the soybean plant at four loci, FAD2-1A and FAD2-1B, oleate desaturase genes and FAD3A and FAD3C, linoleate desaturase genes, and seed oil will not require hydrogenation to prevent oxidation and produce high-quality oil. In 2017 and 2018, a study comparing four near-isogenic lines across multiple Tennessee locations was performed to identify agronomic traits associated with mutations in FAD3A and FAD3C loci, while holding FAD2-1A and FAD2-1B constant in the mutant (high oleic) state. Soybean lines were assessed for yield and oil quality based on mutations at FAD2-1 and FAD3 loci. Variations of wild-type and mutant genotypes were compared at FAD3A and FAD3C loci. Analysis using a generalized linear mixed model in SAS 9.4, indicated no yield drag or other negative agronomic traits associated with the high oleic and low linolenic acid genotype. All four mutations of fad2-1A, fad2-1B, fad3A, and fad3C were determined as necessary to produce a soybean with the new industry standard (>750 g kg⁻¹ oleic and <30 g kg⁻¹ linolenic acid) in a maturity group-IV-Late cultivar for Tennessee growers.     

Inverse identification of constitutive parameters from heat source fields: A local approach applied to hyperelasticity

In this paper, a new inverse identification method of constitutive parameters is developed from full kinematic and thermal field measurements. It consists in reconstructing the heat source field from two different approaches by using the heat diffusion equation. The first one requires the temperature field measurement and the value of the thermophysical parameters. The second one is based on the kinematic field measurement and the choice of a thermo-hyperelastic model that contains the parameters to be identified. The identification is carried out at the local scale, ie, at any point of the heat source field, without using the boundary conditions. In the present work, the method is applied to the challenging case of hyperelasticity from a heterogeneous test. Due to large deformations undergone by the rubber specimen tested, a motion compensation technique is developed to plot the kinematic and the thermal fields at the same points before reconstructing the heterogeneous heat source field. In the present case, the constitutive parameter of the Neo-Hookean model has been identified, and its distribution has been characterized with respect to the strain state at the surface of a cross-shaped specimen.     

Sinusoidal disturbance rejection in chaotic planar oscillators

The main goal of this paper is to design a compensator able to restore the nominal behavior of a planar system, which is rendered chaotic by an unmeasurable sinusoidal disturbance input. To reach such a goal, some instruments, taken from algebraic geometry, are used to estimate the unmeasurable disturbance from the time derivatives of the output of the system and of the control input. Copyright © 2015 John Wiley & Sons, Ltd.     

Impact of the anode operating conditions on the liquid water distribution in the cathode gas diffusion layer

Previous experimental results indicate that the humidification conditions at the anode have an impact on the liquid water distribution in the cathode gas diffusion layer. Numerical simulations are developed to reproduce and analyze this effect. Results consistent with the experimental results are first obtained by playing with the partition coefficients of an advanced pore network model computing the liquid water formation and transfer in the cathode gas diffusion layer (GDL) for a large range of operating conditions. Then, a model for the full anode – cathode assembly is developed by combining the pore network model of the cathode GDL and a 1D model describing the heat and water transfer in the various components of the anode-cathode assembly. This enables one to generalize the dry – wet regime diagram introduced in a previous work by incorporating the effect of the humidity condition at the anode.     

Nonhydrolyzable Heptose Bis- and Monophosphate Analogues Modulate Pro-inflammatory TIFA-NF-κB Signaling

d -Glycero-d -manno-heptose-1β,7-bisphosphate (HBP) and d -glycero-d -manno-heptose-1β-phosphate (H1P) are bacterial metabolites that were recently shown to stimulate inflammatory responses in host cells through the activation of the TIFA-dependent NF-κB pathway. To better understand structure-based activity in relation to this process, a family of nonhydrolyzable phosphonate analogues of HBP and H1P was synthesized. The inflammation modulation by which these molecules induce the TIFA-NF-κB signal axis was evaluated in vivo at a low-nanomolar concentration (6 nM) and compared to that of the natural metabolites. Our data showed that three phosphonate analogues had similar stimulatory activity to HBP, whereas two phosphonates antagonized HBP-induced TIFA-NF-κB signaling. These results open new horizons for the design of pro-inflammatory and innate immune modulators that could be used as vaccine adjuvant.     

Carbon supported bimetallic Ru‐Co catalysts for H2 production through NaBH4 and NH3BH3 hydrolysis

This work investigates the effect of the addition of small amounts of Ru (0.5‐1 wt%) to carbon supported Co (10 wt%) catalysts towards both NaBH₄ and NH₃BH₃ hydrolysis for H₂ production. In the sodium borohydride hydrolysis, the activity of Ru‐Co/carbon catalysts was sensibly higher than the sum of the activities of corresponding monometallic samples, whereas for the ammonia borane hydrolysis, the positive effect of Ru‐Co systems with regard to catalytic activity was less evident. The performances of Ru‐Co bimetallic catalysts correlated with the occurrence of an interaction between Ru and Co species resulting in the formation of smaller ruthenium and cobalt oxide particles with a more homogeneous dispersion on the carbon support. It was proposed that Ru^°, formed during the reduction step of the Ru‐Co catalysts, favors the H₂ activation, thus enhancing the reduction degree of the cobalt precursor and the number of Co nucleation centers. A subsequent reduction of cobalt and ruthenium species also occurs in the hydride reaction medium, and therefore the state of the catalyst before the catalytic experiment determines the state of the active phase formed in situ. The different relative reactivity of the Ru and Co active species towards the two investigated reactions accounted for the different behavior towards NaBH₄ and NH₃BH₃ hydrolysis.     

Geopolymer assembly by emulsion templating: Emulsion stability and hardening mechanisms

This work investigates emulsion templating to synthesize hexadecane oil/geopolymer composites. In a system with hexadecane as the internal (dispersed) phase and an alkali activated continuous phase without added surfactant, adding aluminosilicate clay particles does not increase resistance against creaming or coalescence, while adding a surfactant (L35 or CTAB) stabilizes the solid-liquid interface. Infrared studies and rheological studies of the associated geopolymerization determined that the presence of the organic phase or surfactant has no significant effect on the geopolymerization kinetics, as determined by the change in time of the Si-O-T IR stretching frequency and the rheological moduli involved during the process. The stabilization of the organic template is reminiscent of Pickering emulsion even though we employ a much greater amount of inorganic material for geopolymer formation. Although the addition of surfactant has a significant effect on the behavior of the paste, the percolation of the network remains unmodified, highlighting the fact that the phenomenon is not dependent on viscosity. Finally, rheological measurements were used to obtain the mass fractal dimension of the as-made gel network, which is able to differentiate the interfacial effect between surfactant molecules with a slightly denser interphase when a cationic surfactant is used.     

Automatic fog detection and estimation of visibility distance through use of an onboard camera

In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses. Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition. Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling. Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports. Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety).     

Characterization of Austempered Ductile Iron Through Barkhausen Noise Measurements

The outstanding mechanical properties of austempered ductile irons (ADI) are linked to the microstructure of the matrix obtained by subjecting a ductile iron with an appropriate composition to a heat treatment called austempering. Then the microstructure of the matrix consists of bainitic ferrite with different volume fractions of retained austenite. The aim of this work is to use the magnetic Barkhausen noise (MBN) as a nondestructive method for characterizing the microstructure of ADI. First, it is shown that the amplitude and position of the peak-shaped MBN response is quite sensitive to the microstructure of the matrix of ductile irons. Thus each type of constituent (equiaxial ferrite, pearlite, martensite or bainite) exhibits a typical response and, in turn, it can be identified from the MBN response. Furthermore, a good correlation is found between MBN signal parameters and ADI heat treatment parameters, indicating that MBN is also quite sensitive to fine evolutions of the microstructure of ADI. MBN peak position is especially sensitive to the type of bainite, whereas peak amplitude is linked to the progress of the bainite reaction. Hence MBN measurements appear to be a powerful tool to assess some important microstructural features of ADI castings.