New,simple, and efficient method for the synthesis of N-substituted 4-trifluoromethyl-5-(alkan-1-ol)-pyridin-2(1H)-imines

A new, simple, and efficient method for the synthesis a novel series of 1-substituted 4-(trifluoromethyl)-5-(alkan-1-ol)-pyridin-2(1H)-imines from the reaction of 3-(5,6-dihydro-4H-pyran-3-yl)-4,4,4-trifluorobut-2-enenitrile and 3-(4,5-dihydrofuran-3-yl)-4,4,4-trifluorobut-2-enenitrile with primary amines – is described. The products were obtained in 29–82% yield.     

Immobilization and Stabilization of Beta-Xylosidases from Penicillium janczewskii

β-Xylosidases are critical for complete degradation of xylan, the second main constituent of plant cell walls. A minor β-xylosidase (BXYL II) from Penicillium janczewskii was purified by ammonium sulfate precipitation (30% saturation) followed by DEAE-Sephadex chromatography in pH 6.5 and elution with KCl. The enzyme presented molecular weight (MW) of 301 kDa estimated by size exclusion chromatography. Optimal activity was observed in pH 3.0 and 70–75 °C, with higher stability in pH 3.0–4.5 and half-lives of 11, 5, and 2 min at 65, 70, and 75 °C, respectively. Inhibition was moderate with Pb⁺² and citrate and total with Cu⁺², Hg⁺², and Co⁺². Partially purified BXYL II and BXYL I (the main β-xylosidase from this fungus) were individually immobilized and stabilized in glyoxyl agarose gels. At 65 °C, immobilized BXYL I and BXYL II presented half-lives of 4.9 and 23.1 h, respectively, therefore being 12.3-fold and 33-fold more stable than their unipuntual CNBr derivatives (reference mimicking soluble enzyme behaviors). During long-term incubation in pH 5.0 at 50 °C, BXYL I and BXYL II glyoxyl derivatives preserved 85 and 35% activity after 25 and 7 days, respectively. Immobilized BXYL I retained 70% activity after 10 reuse cycles of p-nitrophenyl-β-D-xylopyranoside hydrolysis.

     

Residual stress field and reduction of stress intensity factors in cold-worked holes

Closed-form and semi-analytical solutions are obtained for the residual stress distributions in a plate caused by pressure acting on a central circular hole, representing the cold-work process. The material is elastic–perfectly plastic. Both Tresca and von Mises yield criteria are used and the corresponding residual stress distributions are compared. The relation between the dimension of the plastic zone and the value of internal pressure is presented. The relation between the magnitude of the residual stresses and the remote uniform tensile stress required to open symmetrical radial cracks is also presented. The reduction of the stress intensity factors of cracked open and riveted holes as a function of the internal pressure applied (or mandrel radial displacement) is investigated using numerical models for both an elastic–perfectly plastic material and for an Al 2024-T3 Alclad aluminum alloy.     

Application of X-ray diffraction, micromagnetic and hole drilling methods for residual stress determination in a ball bearing steel ring

A basic understanding of distortion problems requires the analysis of a complete manufacturing process including an almost complete overview of residual stress states in the component during each production step. To reduce the measurement time in the future, three measurements methods (X-ray diffraction, micromagnetic and blind hole drilling methods) have been used to analyze residual stress states in machined AISI 52100 ball bearing rings. X-ray diffraction was used as a state-of-the-art method for machining induced residual stresses with pronounced gradients. The ring exhibited a complex residual stress state with high tensile residual stresses at the surface, a strong gradient in depth, and also showed some variation along the outer circumference due to a superimposition of machining induced residual stresses and effects from the clamping device process. Due to this surface state, micromagnetic signals depend on the analyzing frequency. A calibration of the signals was only possible with the X-ray diffraction data. The results of the three different measurement methods correlate reasonably well.     

Computational performance and cross‐validation error precision of five PLS algorithms using designed and real data sets

An evaluation of computational performance and precision regarding the cross‐validation error of five partial least squares (PLS) algorithms (NIPALS, modified NIPALS, Kernel, SIMPLS and bidiagonal PLS), available and widely used in the literature, is presented. When dealing with large data sets, computational time is an important issue, mainly in cross‐validation and variable selection. In the present paper, the PLS algorithms are compared in terms of the run time and the relative error in the precision obtained when performing leave‐one‐out cross‐validation using simulated and real data sets. The simulated data sets were investigated through factorial and Latin square experimental designs. The evaluations were based on the number of rows, the number of columns and the number of latent variables. With respect to their performance, the results for both simulated and real data sets have shown that the differences in run time are statistically different. PLS bidiagonal is the fastest algorithm, followed by Kernel and SIMPLS. Regarding cross‐validation error, all algorithms showed similar results. However, in some situations as, for example, when many latent variables were in question, discrepancies were observed, especially with respect to SIMPLS. Copyright © 2010 John Wiley & Sons, Ltd.     

Evaluation of the effects of Candidatus Liberibacter asiaticus on inoculated citrus plants using laser-induced breakdown spectroscopy (LIBS) and chemometrics tools

This study investigated the organic and inorganic constituents of healthy leaves and Candidatus Liberibacter asiaticus (CLas)-inoculated leaves of citrus plants. The bacteria CLas are one of the causal agents of citrus greening (or Huanglongbing) and its effect on citrus leaves was investigated using laser-induced breakdown spectroscopy (LIBS) combined with chemometrics. The information obtained from the LIBS spectra profiles with chemometrics analysis was promising for the construction of predictive models to identify healthy and infected plants. The major, macro- and microconstituents were relevant for differentiation of the sample conditions. The models were then applied to different inoculation times (from 1 to 8 months). The models were effective in the classification of 82-97% of the diseased samples with a 95% significance level. The novelty of this method was in the fingerprinting of healthy and diseased plants based on their organic and inorganic contents.     

Crosslink effect and albumin adsorption onto chitosan/alginate multilayered systems: an in situ QCM-D study

The adsorption of HSA onto CHI/ALG multilayer assemblies was assessed in situ using QCM-D. It was found that the behavior of HSA on biomaterials surface can be tuned by adjusting parameters of the polyelectrolyte system such as pH, layer number, crosslinker and polymer terminal layer. Our results confirmed the key role of electrostatic interactions during HSA adsorption, since oppositely charged surfaces were more effective in promoting protein adhesion. QCM-D data revealed that crosslinking (CHI/ALG)(5) CHI films allows HSA to become adsorbed in physiological conditions. Our results suggested that the biological potential of biopolymers and the mild conditions of the LbL technique turn these natural nanoassemblies into a suitable choice to be used as pH-sensitive coatings.     

Palladium-catalyzed reductive ortho-arylation: evidence for the decomposition of 1,2-dimethoxyethane and subsequent arylpalladium(II) reduction

A palladium-catalyzed crossed biaryl coupling/reduction sequence enables the formation of meta-substituted biaryls via solvent-mediated arylpalladium(II) reduction. Isotope labeling studies determined that the decomposition of 1,2-dimethoxyethane (DME) is indeed involved in the reductive process.     

Evaluation of standard and advanced preprocessing methods for the univariate analysis of blood serum 1H-NMR spectra

Proton nuclear magnetic resonance (¹H-NMR)-based metabolomics enables the high-resolution and high-throughput assessment of a broad spectrum of metabolites in biofluids. Despite the straightforward character of the experimental methodology, the analysis of spectral profiles is rather complex, particularly due to the requirement of numerous data preprocessing steps. Here, we evaluate how several of the most common preprocessing procedures affect the subsequent univariate analyses of blood serum spectra, with a particular focus on how the standard methods perform compared to more advanced examples. Carr–Purcell–Meiboom–Gill 1D ¹H spectra were obtained for 240 serum samples from healthy subjects of the Asklepios study. We studied the impact of different preprocessing steps—integral (standard method) and probabilistic quotient normalization; no, equidistant (standard), and adaptive-intelligent binning; mean (standard) and maximum bin intensity data summation—on the resonance intensities of three different types of metabolites: triglycerides, glucose, and creatinine. The effects were evaluated by correlating the differently preprocessed NMR data with the independently measured metabolite concentrations. The analyses revealed that the standard methods performed inferiorly and that a combination of probabilistic quotient normalization after adaptive-intelligent binning and maximum intensity variable definition yielded the best overall results (triglycerides, R = 0.98; glucose, R = 0.76; creatinine, R = 0.70). Therefore, at least in the case of serum metabolomics, these or equivalent methods should be preferred above the standard preprocessing methods, particularly for univariate analyses. Additional optimization of the normalization procedure might further improve the analyses.