Application of Artificial Neural Networks (ANNs) in Wine Technology

In recent years, neural networks have turned out as a powerful method for numerous practical applications in a wide variety of disciplines. In more practical terms neural networks are one of nonlinear statistical data modeling tools. They can be used to model complex relationships between inputs and outputs or to find patterns in data. In food technology artificial neural networks (ANNs) are useful for food safety and quality analyses, predicting chemical, functional and sensory properties of various food products during processing and distribution. In wine technology, ANNs have been used for classification and for predicting wine process conditions. This review discusses the basic ANNs technology and its possible applications in wine technology.     

Conductive polyaniline–polythiophene/poly(ethylene terephthalate) composite fiber: Effects of pH and washing processes on surface resistivity

A conductive polyaniline (PAn)–polythiophene (PTh)/poly(ethylene terephthalate) (PET) composite fiber was prepared by polymerization of aniline and thiophene in the presence of PET fibers in an organic medium with FeCl₃. The effects of polymerization conditions, such as polymerization medium, mol ratios of aniline/thiophene and FeCl₃/aniline‐thiophene as well as polymerization temperature and time, were investigated on PAn–PTh content (%) and surface resistivity of the composite. The composite with the lowest surface resistivity (1.30 MΩ/cm²) was obtained by polymerization of aniline and thiophene (1/3 mol ratio) in acetonitrile/chloroform (1/5 volume ratio) at 20°C. The surface resistivity of the PAn–PTh/PET composite containing 4.8% PAn–PTh was increased from 1.9 MΩ/cm² to 270 MΩ/cm² at pH 11. The washing durability of the composites was determined with domestic and commercial laundering processes by monitoring the surface resistivity and morphology. The composite was also characterized with FTIR, TGA, elemental analysis, optic microscope and SEM techniques. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41979.     

Microstructural properties of lithium-added cement mortars subjected to alkali–silica reactions

Little comparative research has been done on the efficiency of lithium additives to reduce the alkali–silica reaction (ASR) expansion. To reduce the ASR effects of reactive aggregate, different mortar bars were obtained by adding lithium additives (Li₂SO₄, LiNO₃, Li₂CO₃, LiBr and LiF) to the mixing water by the following mass percentages of cement: 0%, 0.5%, 1%, 1.5%, 2%, 2.5% and 3%. The ASR expansions of the mortar bars at 2, 7 and 14 days were identified according to ASTM C 1260-14. The morphology of the specimens subject to the ASR effect was analysed using a scanning electron microscope, and their chemical composition was analysed by electron dispersion spectroscopy. Among all specimens, the lowest level of 14-day ASR expansion was obtained in mortar bars with 3% Li₂CO₃ additive.     

Chemometric and phenolic attributes of blended wines assessed by multivariate techniques

The aim of the study was to investigate the quality of blended wines produced from Vitis vinifera L. Cabernet Sauvignon, Merlot and Sauvignon blanc grapes. Wines were processed according to accepted conventional methods for white and red wines. Blended wines were produced with different ranges (25, 50, 75 and 100%) of Cabernet Sauvignon, Merlot and Sauvignon blanc wines. Produced wines were evaluated for total phenols (mg/L), total tartaric esters (mg/L caffeic acid), total flavonols (mg/L quercetin), chemometric parameters such as D280%, D420%, D520%, D620%, dA%, CD%, T, CI%, R%, Y% and B%, CIELAB parameters, protein, total and volatile acidity. Analyses on an n‐dimensional scale demonstrated the relationships among the wines of different grape origins and different blending ratios. On the basis of these differences, two main groups were plotted using principal component analysis and cluster analysis. The results demonstrate the possibilities of optimizing wines on the basis of defined parameters. Copyright © 2015 The Institute of Brewing & Distilling     

Evaluation of methods for DNA extraction from must and wine

The quality of wine depends on many factors. One of the most important is the selection of appropriate and defined grape varieties. The analysis of phenolic compounds, amino acids, trace elements and isotopes of wines, used for the identification of grapes varieties, is not sufficient and requires a lengthy analysis period. The development of molecular techniques such as restriction fragment length polymorphism, random amplified polymorphic DNA and microsatellites provides opportunities for the differentiation of grape varieties. In this regard, the use of DNA extracted from must and wine appears to be a good marker for the identification of grape varieties used in wine production. In this study, DNA was extracted from grape, leaf, must and wine samples of Vitis vinifera L. cv. Cabernet Sauvignon, Merlot and Sauvignon Blanc origin and examined using different extraction methods. Of the DNA extraction methods tested, the method using absorption at 260/280 nm (with values of 0.19 and 1.92) was considered the method of choice. Copyright © 2014 The Institute of Brewing & Distilling     

对房屋抗震评估中采用的非线性静力分析方法的评估

基于设计的性能分析方法的一个关键部分是,对地震需求谱参数的准确采用。非线性静力方法(NSPs)现在广泛应用在工程实践上,主要用于预测房屋建筑的抗震能力。利用NSPs,地震需求谱可以从特定地点的危险性谱中直接计算出来,而非线性时程分析需要全部地面运动和针对地震记录可变性的相关性评估。除此之外,基于恒载模式(ATC-40和FEMA-356中所推荐的)NSP简化版本有条文说明其无法考虑由结构弹塑性而导致的更高模态效应以及模态变化。因此,研究者纷纷提出解决了以上缺点的改进Pushover法。通过对典型的钢结构和钢筋混凝土结构的突出反应特征与一套全面的NTH分析中得到的基准反应的比较,研究了多种非线性静力分析方法(NSPs)的有效性。更重要的是,考虑到多种地面运动特征,还采用了一组从普通的远断层记录到近断层地面运动的时间序列。这项分析研究的结果显示,较之该项研究中的其他非线性分析方法,适应性组合模型方法可以更为准确地预测如层间位移、塑性角等的极值。     

Preparation of chitosan‐coated magnetite nanoparticles and application for immobilization of laccase

In this study, immobilization of laccase (L) enzyme on magnetite (Fe₃O₄) nanoparticles was achieved, so that the immobilized enzyme could be used repeatedly. For this purpose, Fe₃O₄ nanoparticles were coated and functionalized with chitosan (CS) and laccase from Trametes versicolor was immobilized onto chitosan‐coated magnetic nanoparticles (Fe₃O₄‐CS) by adsorption or covalent binding after activating the hydroxyl groups of chitosan with carbodiimide (EDAC) or cyanuric chloride (CC). For chitosan‐coated magnetic nanoparticles, the thickness of CS layer was estimated as 1.0–4.8 nm by TEM, isoelectric point was detected as 6.86 by zeta (ζ)‐potential measurements, and the saturation magnetization was determined as 25.2 emu g^?1 by VSM, indicating that these nanoparticles were almost superparamagnetic. For free laccase and immobilized laccase systems, the optimum pH, temperature, and kinetic parameters were investigated; and the change of the activity against repeated use of the immobilized systems were examined. The results indicated that all immobilized systems retained more than 71% of their initial activity at the end of 30 batch uses. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Using multi-modal 3D contours and their relations for vision and robotics

In this work, we make use of 3D contours and relations between them (namely, coplanarity, cocolority, distance and angle) for four different applications in the area of computer vision and vision-based robotics. Our multi-modal contour representation covers both geometric and appearance information. We show the potential of reasoning with global entities in the context of visual scene analysis for driver assistance, depth prediction, robotic grasping and grasp learning. We argue that, such 3D global reasoning processes complement widely-used 2D local approaches such as bag-of-features since 3D relations are invariant under camera transformations and 3D information can be directly linked to actions. We therefore stress the necessity of including both global and local features with different spatial dimensions within a representation. We also discuss the importance of an efficient use of the uncertainty associated with the features, relations, and their applicability in a given context.