Novel aromatic carboxamides from dehydroabietylamine as potential fungicides: Design,synthesis and antifungal evaluation

The present study was carried out to design and synthesize a number of novel aromatic carboxamide derivatives of dehydroabietylamine. The preliminary antifungal assay indicated that most of title compounds displayed moderate to good antifungal activity toward the six fungal strains in vitro. Compounds 3i, 3q, 4b and 4d showed significant antifungal activity against Sclerotinia sclerotiorum, with EC₅₀ values ranging from 0.067 ～ 0.393 mg/L. Compounds 3i, 4b and 4d also showed pronounced mycelial growth inhibition activities against B. cinerea and A. solani. Furthermore, in the in vivo assay, compound 4b exhibited brilliant protective activity against S. sclerotiorum-infected rape leaves. Meanwhile, the in vivo bioassay on tomato plants infected by B. cinerea showed that compound 3i and 4d displayed excellent protective activity at 200 mg/L, which were near to boscalid. Primary mechanistic study revealed that 4b could inhibit sclerotia formation as well as reduce the exopolysaccharide level. SEM and TEM analysis indicated that 4b possessed a strong ability to destroy the surface morphology of mycelia, cell structure and seriously interfere with the growth of the fungal pathogen. In addition, 4b exhibited good inhibitory activity (IC₅₀ = 23.3 ± 1.6 μM) toward succinate dehydrogenase (SDH). Molecular modeling study confirmed the binding modes between compound 4b and SDH. The above antifungal results and fungicidal mechanism study revealed that this class of dehydroabietylamine derivatives could be potential SDH inhibitors and lead compounds for novel fungicides development.     

Recognition of polymer-particle interfacial morphology in mixed matrix membranes through ideal permeation predictive models

Interfacial properties play an important role in determining characteristics and performance of composite materials, especially in membrane gas separation applications. Formation of any undesirable defect at polymer-particle interface can directly influence on membrane permeability and selectivity in addition to unwanted effects on the other mechanical/physical properties. For achieving a quick insight about the role and nature of interfacial morphologies in mixed matrix membranes (MMMs) and their effects on gas transport properties, a new technique mainly in terms of mathematical modeling was developed. Based on the proposed approach, although ideal models often failed in predicting MMMs performance, these models can provide guidelines for discernment of the types of formed interfacial morphology, like current methods in characterization.     

Reverse fragment based drug discovery approach via simple estimation of fragment contributions

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Spatiotemporal model for the progression of transgressive dunes

Transgressive dune fields, which are active sand areas surrounded by vegetation, exist on many coasts. In some regions like in Fraser Island in Australia, small dunes shrink while large ones grow, although both experience the same climatic conditions. We propose a general mathematical model for the spatiotemporal dynamics of vegetation cover on sand dunes and focus on the dynamics of transgressive dunes. Among other possibilities, the model predicts growth parallel to the wind with shrinkage perpendicular to the wind, where, depending on geometry and size, a transgressive dune can initially grow although eventually shrink. The larger is the initial area the slower its stabilization process. The model’s predictions are supported by field observations from Fraser Island in Australia.     

Unsupervised cell identification on multidimensional X‐ray fluorescence datasets

A novel approach to locate, identify and refine positions and whole areas of cell structures based on elemental contents measured by X‐ray fluorescence microscopy is introduced. It is shown that, by initializing with only a handful of prototypical cell regions, this approach can obtain consistent identification of whole cells, even when cells are overlapping, without training by explicit annotation. It is robust both to different measurements on the same sample and to different initializations. This effort provides a versatile framework to identify targeted cellular structures from datasets too complex for manual analysis, like most X‐ray fluorescence microscopy data. Possible future extensions are also discussed.     

Probabilistic approaches to compute uncertainty intervals and sensitivity factors of ultrasonic simulations of a weld inspection

For comprehension purpose, numerical computations are more and more used to simulate the propagation phenomena observed during experimental inspections. However, the good agreement between experimental and simulated data necessitates the use of accurate input data and thus a good characterization of the inspected material. Generally the input data are provided by experimental measurements and are consequently tainted with uncertainties. Thus, it becomes necessary to evaluate the impact of these uncertainties on the outputs of the numerical model. The aim of this study is to perform a probabilistic analysis of an ultrasonic inspection of an austenitic weld containing a manufactured defect based on advanced techniques such as polynomial chaos expansions and computation of sensitivity factors (Sobol, DGSM). The simulation of this configuration with the finite element code ATHENA2D was performed 6000 times with variations of the input parameters (the columnar grain orientation and the elastic constants of the material). The 6000 sets of input parameters were obtained from adapted statistical laws. The output parameters (the amplitude and the position of the defect echo) distributions were then analyzed and the 95% confidence intervals were determined.     

How good is CuAAC “click” chemistry for polymer coupling reactions?

¹H NMR and SEC analyses are used to investigate the overall efficiency of Copper Catalyzed Azide Alkyne Cycloaddition (CuAAC) “click” coupling reactions between alkyne‐ and azide‐terminated polymers using polystyrene as a model. Quantitative convolution modeling of the entire molecular weight distribution is applied to characterize the outcomes of the functional polymer synthesis reactions (i.e., by atom transfer radical polymerization), as well as the CuAAC coupling reaction. Incomplete functionality of the azide‐terminated polystyrene (∼92%) proves to be the largest factor compromising the efficacy of the CuAAC coupling reaction and is attributed primarily to the loss of terminal bromide functionality during its synthesis. The efficiency of the S_N2 reaction converting bromide to azide was found to be about 99%. After taking into account the influence of non‐functional polymer, we find that, under the reaction conditions used, the efficiency of the CuAAC coupling reaction determined from both techniques is about 94%. These inefficiencies compromise the fidelity and potential utility of CuAAC coupling reactions for the synthesis of hierarchically structured polymers. While CuAAC efficiency is expected to depend on the specific reaction conditions used, the framework described for determining reaction efficiency does provide a means for ultimately optimizing the reaction conditions for CuAAC coupling reactions. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2018 , 56, 75–84     

Signal modeling using the gradient search

This letter presents a new method for continuous signal modeling. Firstly, the continuous signal can be represented as a function of the trigonometric functional extension (Fourier series). Fourier series of the signal are parameterized by the fundamental frequency and unknown parameters. Then, the gradient-based iterative identification algorithm is derived, for estimating parameters of the signal model with known and unknown frequencies, separately. Finally, the simulation results indicate that the proposed algorithm is effective.     

Comparing the mechanical response of di‐, tri‐, and tetra‐functional resin epoxies with reactive molecular dynamics

The influence of monomer functionality on the mechanical properties of epoxies is studied using molecular dynamics (MD) with the Reax Force Field (ReaxFF). From deformation simulations, the Young's modulus, yield point, and Poisson's ratio are calculated and analyzed. Comparison between the network structures of distinct epoxies is further advanced by the monomeric degree index (MDI). Experimental validation demonstrates the MD results correctly predict the relationship in Young's moduli. Therefore, ReaxFF is confirmed to be a useful tool for studying the mechanical behavior of epoxies. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2018 , 56, 255–264