Water-Based Graphene Oxide–Silicon Hybrid Nanofluids—Experimental and Theoretical Approach

In the current paper, a new hybrid nanofluid based on graphene oxide sheets and silicon nanoparticles is proposed for thermal applications. GO sheets and Si nanoparticles with different mixture ratios are dispersed in distilled water. Dynamic viscosity is measured at temperatures within the range 20–50 °C and the values are compared to the results available in the literature. The results indicated that the viscosity increases with increasing the mixture ratio of graphene oxide. A new correlation for the dynamic viscosity based on the experimental findings is proposed. Finally, the criteria for the performance of new hybrid nanofluid for thermal applications are analyzed.     

Diamine oxidase supplementation improves symptoms in patients with histamine intolerance

Food Science and Biotechnology - Histamine intolerance (HIT) is thought to be caused by a disproportionate amount of histamine in the body. The enzyme diamine oxidase (DAO) is considered for the...     

Efficient document image binarization using heterogeneous computing and parameter tuning

In the context of historical document analysis, image binarization is a first important step, which separates foreground from background, despite common image degradations, such as faded ink, stains, or bleed-through. Fast binarization has great significance when analyzing vast archives of document images, since even small inefficiencies can quickly accumulate to years of wasted execution time. Therefore, efficient binarization is especially relevant to companies and government institutions, who want to analyze their large collections of document images. The main challenge with this is to speed up the execution performance without affecting the binarization performance. We modify a state-of-the-art binarization algorithm and achieve on average a 3.5 times faster execution performance by correctly mapping this algorithm to a heterogeneous platform, consisting of a CPU and a GPU. Our proposed parameter tuning algorithm additionally improves the execution time for parameter tuning by a factor of 1.7, compared to previous parameter tuning algorithms. We see that for the chosen algorithm, machine learning-based parameter tuning improves the execution performance more than heterogeneous computing, when comparing absolute execution times.

     

Fusarium graminearum Infection Strategy in Wheat Involves a Highly Conserved Genetic Program That Controls the Expression of a Core Effectome

Fusarium graminearum, the main causal agent of Fusarium Head Blight (FHB), is one of the most damaging pathogens in wheat. Because of the complex organization of wheat resistance to FHB, this pathosystem represents a relevant model to elucidate the molecular mechanisms underlying plant susceptibility and to identify their main drivers, the pathogen’s effectors. Although the F. graminearum catalog of effectors has been well characterized at the genome scale, in planta studies are needed to confirm their effective accumulation in host tissues and to identify their role during the infection process. Taking advantage of the genetic variability from both species, a RNAseq-based profiling of gene expression was performed during an infection time course using an aggressive F. graminearum strain facing five wheat cultivars of contrasting susceptibility as well as using three strains of contrasting aggressiveness infecting a single susceptible host. Genes coding for secreted proteins and exhibiting significant expression changes along infection progress were selected to identify the effector gene candidates. During its interaction with the five wheat cultivars, 476 effector genes were expressed by the aggressive strain, among which 91% were found in all the infected hosts. Considering three different strains infecting a single susceptible host, 761 effector genes were identified, among which 90% were systematically expressed in the three strains. We revealed a robust F. graminearum core effectome of 357 genes expressed in all the hosts and by all the strains that exhibited conserved expression patterns over time. Several wheat compartments were predicted to be targeted by these putative effectors including apoplast, nucleus, chloroplast and mitochondria. Taken together, our results shed light on a highly conserved parasite strategy. They led to the identification of reliable key fungal genes putatively involved in wheat susceptibility to F. graminearum, and provided valuable information about their putative targets.     

Growth and characterization of gold catalyzed SiGe nanowires and alternative metal-catalyzed Si nanowires

The growth of semiconductor (SC) nanowires (NW) by CVD using Au-catalyzed VLS process has been widely studied over the past few years. Among others SC, it is possible to grow pure Si or SiGe NW thanks to these techniques. Nevertheless, Au could deteriorate the electric properties of SC and the use of other metal catalysts will be mandatory if NW are to be designed for innovating electronic. First, this article's focus will be on SiGe NW's growth using Au catalyst. The authors managed to grow SiGe NW between 350 and 400°C. Ge concentration (x) in Si1-xGex NW has been successfully varied by modifying the gas flow ratio: R = GeH4/(SiH4 + GeH4). Characterization (by Raman spectroscopy and XRD) revealed concentrations varying from 0.2 to 0.46 on NW grown at 375°C, with R varying from 0.05 to 0.15. Second, the results of Si NW growths by CVD using alternatives catalysts such as platinum-, palladium- and nickel-silicides are presented. This study, carried out on a LPCVD furnace, aimed at defining Si NW growth conditions when using such catalysts. Since the growth temperatures investigated are lower than the eutectic temperatures of these Si-metal alloys, VSS growth is expected and observed. Different temperatures and HCl flow rates have been tested with the aim of minimizing 2D growth which induces an important tapering of the NW. Finally, mechanical characterization of single NW has been carried out using an AFM method developed at the LTM. It consists in measuring the deflection of an AFM tip while performing approach-retract curves at various positions along the length of a cantilevered NW. This approach allows the measurement of as-grown single NW's Young modulus and spring constant, and alleviates uncertainties inherent in single point measurement.     

Quantitative Prediction of Steatosis in Patients with Non-Alcoholic Fatty Liver by Means of Hepatic MicroRNAs Present in Serum and Correlating with Hepatic Fat

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent form of chronic liver disease worldwide, but a reliable non-invasive method to quantify liver steatosis in primary healthcare is not available. Circulating microRNAs have been proposed as biomarkers of severe/advanced NAFLD (steatohepatitis and fibrosis). However, the use of circulating miRNAs to quantitatively assess the % of liver fat in suspected NAFLD patients has not been investigated. We performed global miRNA sequencing in two sets of samples: human livers from organ donors (n = 20), and human sera from biopsy-proven NAFLD patients (n = 23), both with a wide range of steatosis quantified in their liver biopsies. Partial least squares (PLS) regression combined with recursive feature elimination (RFE) was used to select miRNAs associated with steatosis. Moreover, regression models with only 2 or 3 miRNAs, with high biological relevance, were built. Comprehensive microRNA sequencing of liver and serum samples resulted in two sets of abundantly expressed miRNAs (418 in liver and 351 in serum). Pearson correlation analyses indicated that 18% of miRNAs in liver and 14.5% in serum were significantly associated with the amount of liver fat. PLS-RFE models demonstrated that 50 was the number of miRNAs providing the lowest error in both liver and serum models predicting steatosis. Comparison of the two miRNA subsets showed 19 coincident miRNAs that were ranked according to biological significance (guide/passenger strand, relative abundance in liver and serum, number of predicted lipid metabolism target genes, correlation significance, etc.). Among them, miR-10a-5p, miR-98-5p, miR-19a-3p, miR-30e-5p, miR-32-5p and miR-145-5p showed the highest biological relevance. PLS regression models with serum levels of 2–3 of these miRNAs predicted the % of liver fat with errors <5%.     

Investigations of ductile damage during the process chains of toothed functional components manufactured by sheet-bulk metal forming

Sheet-bulk metal forming processes combine conventional sheet forming processes with bulk forming of sheet semi-finished parts. In these processes the sheets undergo complex forming histories. Due to in- and out-of-plane material flow and large accumulated plastic strains, the conventional failure prediction methods for sheet metal forming such as forming limit curve fall short. As a remedy, damage models can be applied to model damage evolution during those processes. In this study, damage evolution during the production of two different toothed components from DC04 steel is investigated. In both setups, a deep drawn cup is upset to form a circumferential gearing. However, the two final products have different dimensions and forming histories. Due to combined deep drawing and upsetting processes, the material flow on the cup walls is three-dimensional and non-proportional. In this study, the numerical and experimental investigations for those parts are presented and compared. Damage evolution in the process chains is simulated with a Lemaitre damage criterion. Microstructural analysis by scanning electron microscopy is performed in the regions with high mechanical loading. It is observed that the evolution of voids in terms of void volume fraction is strongly dependent on the deformation path. The comparison of simulation results with microstructural data shows that the void volume fraction decreases in the upsetting stage after an initial increase in the drawing stage. Moreover, the concurrent numerical and microstructural analysis provides evidence that the void volume fraction decreases during compression in sheet-bulk metal forming.     

Interactions between immunoglobulin-like and catalytic modules in Clostridium thermocellum cellulosomal cellobiohydrolase CbhA

Cellobiohydrolase CbhA from Clostridium thermocellum cellulosome is a multi-modular protein composed starting from the N-terminus of a carbohydrate-binding module (CBM) of family 4, an immunoglobulin(Ig)-like module, a catalytic module of family 9 glycoside hydrolases (GH9), X1(1) and X1(2) modules, a CBM of family 3 and a dockerin module. Deletion of the Ig-like module from the Ig-GH9 construct results in complete inactivation of the GH9 module. The crystal structure of the Ig-GH9 module pair reveals the existence of an extensive module interface composed of over 40 amino acid residues of both modules and maintained through a large number of hydrophilic and hydrophobic interactions. To investigate the importance of these interactions between the two modules, we compared the secondary and tertiary structures and thermostabilities of the individual Ig-like and GH9 modules and the Ig-GH9 module pair using both circular dichroism (CD) spectroscopy and differential scanning calorimetry (DSC). Thr230, Asp262 and Asp264 of the Ig-like module are located in the module interface of the Ig-GH9 module pair and are suggested to be important in 'communication' between the modules. These residues were mutated to alanyl residues. The structure, stability and catalytic properties of the native Ig-GH9 and its D264A and T230A/D262A mutants were compared. The results indicate that despite being able to fold relatively independently, the Ig-like and GH9 modules interact and these interactions affect the final fold and stability of each module. Mutations of one or two amino acid residues lead to destabilization and change of the mechanism of thermal unfolding of the polypeptides. The enzymatic properties of native Ig-GH9, D264A and T230A/D262A mutants are similar. The results indicate that inactivation of the GH9 module occurs as a result of multiple structural disturbances finally affecting the topology of the catalytic center.     

Bonded aerospace repairs under tensile loading: Wet chemical surface treatment and selected environmental conditions

Repair of composite structures and the impact of demanding environmental conditions is a crucial issue for the aircraft industry because of the increasing use of composites in modern aircraft. Consequently, the impact of environmental conditions common for aircraft applications on repair specimens in comparison to nonrepaired specimens is studied. All specimens are produced from a woven carbon fiber-reinforced epoxy-based prepreg. For the repair-specimens, an epoxy-based film adhesive is used for the soft patch repair approach. During the repair process, the surface of the precured prepreg is prepared by a mechanical method (sanding) and an additional chemical functionalization, respectively. Moisture absorption of the repair specimens is independent of the surface preparation method and higher for the repaired than for the nonrepaired specimens. The key influencing environmental conditions for the tensile strength and the failure mode of the repair specimens are elevated temperature testing as well as hot/wet conditioning and conditioning in deionized water. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47506.