Third Generation Buchwald Precatalysts with XPhos and RuPhos: Multigram Scale Synthesis,Solvent-Dependent Isomerization of XPhos Pd G3 and Quality Control by 1H- and 31P-NMR Spectroscopy

The third generation Buchwald precatalysts Pd(ABP)(Phos)(OMs) (also known as Phos Pd G3)) with XPhos and RuPhos were prepared in multigram scale by a modified procedure (ABP = fragment of C-deprotonated 2-aminobiphenyl, XPhos = 2-dicyclohexylphosphino-2′,4′,6′-triisopropylbiphenyl, RuPhos = 2-dicyclohexylphosphino-2′,6′-diisopropoxybiphenyl, OMs⁻ = CH₃SO₃⁻). The ¹H- and ³¹P-NMR spectra of the title complexes and some impurities, measured by various 1D and 2D techniques, were analyzed in detail. The solvent-dependent isomerization of Pd(ABP)(XPhos)(OMs) was studied by NMR, and the X-ray structures of two isomers were determined. The impurities in precatalysts, such as Pd(ABP)(HABP)(OMs) (HABP—neutral 2-aminobiphenyl coordinated to Pd²⁺ in N-monodentate mode) and PdCl₂(XPhos)₂, were identified and characterized by single crystal X-ray diffraction. A simple method for the quick quality control (QC) of the precatalysts, suitable for routine use, was proposed. The method was based on the assessment of the impurity content on the basis of the ¹H-NMR spectra analysis.     

Effect of Botanical Extracts on the Growth and Nutritional Quality of Field-Grown White Head Cabbage (Brassica oleracea var. capitata)

Nutraceuticals and functional foods are gaining more attention amongst consumers interested in nutritious food. The consumption of foodstuffs with a high content of phytochemicals has been proven to provide various health benefits. The application of biostimulants is a potential strategy to fortify cultivated plants with beneficial bioactive compounds. Nevertheless, it has not yet been established whether the proposed higher plants (St. John’s wort, giant goldenrod, common dandelion, red clover, nettle, and valerian) are appropriate for the production of potential bio-products enhancing the nutritional value of white cabbage. Therefore, this research examines the impact of botanical extracts on the growth and nutritional quality of cabbage grown under field conditions. Two extraction methods were used for the production of water-based bio-products, namely: ultrasound-assisted extraction and mechanical homogenisation. Bio-products were applied as foliar sprays to evaluate their impact on total yield, dry weight, photosynthetic pigments, polyphenols, antioxidant activity, vitamin C, nitrates, micro- and macroelements, volatile compounds, fatty acids, sterols, and sugars. Botanical extracts showed different effects on the examined parameters. The best results in terms of physiological and biochemical properties of cabbage were obtained for extracts from common dandelion, valerian, nettle, and giant goldenrod. When enriched with nutrients, vegetables can constitute a valuable component of functional food.     

Evaluation of Physiological Characteristics,Soluble Sugars,Organic Acids and Volatile Compounds in ‘Orin’ Apples (Malus domestica) at Different Ripening Stages

‘Orin’ is a popular apple cultivar, which has a yellow-green appearance, pleasant taste, and unique aroma. However, few studies on the fruit quality characteristics of ‘Orin’ apples have been reported before. In this study, changes of the physiological characteristics were measured at different ripening stages, and the soluble sugars and organic acids were determined by high-performance liquid chromatography (HPLC). Volatile compounds were identified using the headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). During the fruit ripening, the ‘Orin’ apple fruit weight, size, and total soluble solid were gradually increased by contrast with the titratable acidity, and the firmness decreased. The content of four soluble sugars reached the maximum at the 180 days after full bloom (DAFB) stage. Malic acid was measured as the most abundant organic acid in ‘Orin’ apples. Ethyl butyrate, hexyl propanoate, hexyl acetate and butyl acetate belonging to esters with high odor activity values (OAVs) could be responsible for the typical aroma of ‘Orin’ apples. The aim of this work was to provide information on the flavor characteristics of ‘Orin’ apples and promote this apple cultivar for marketing and processing in the future.     

Bioactive Phenolic Compounds from Primula veris L.: Influence of the Extraction Conditions and Purification

Our experiments may help to answer the question of whether cowslip (Primula veris L.) is a rich source of bioactive substances that can be obtained by efficient extraction with potential use as a food additive. A hypothesis assumed that the type of solvent used for plant extraction and the individual morphological parts of Primula veris L. used for the preparation of herbal extracts will have key impacts on the efficiency of the extraction of bioactive compounds, and thus, the health-promoting quality of plant concentrates produced. Most analysis of such polyphenolic compound contents in extracts from Primula veris L. has been performed by using chromatography methods such as ultra-performance reverse-phase liquid chromatography (UPLC−PDA−MS/MS). Experiments demonstrated that the most effective extraction agent for fresh study material was water at 100 °C, whereas for dried material it was 70% ethanol. The richest sources of polyphenolic compounds were found in cowslip primrose flowers and leaves. The aqueous and ethanol extracts from Primula veris L. were characterized by a quantitatively rich profile of polyphenolic substances, and a high antioxidative potential. Selective extraction with the use of mild conditions and neutral solvents is the first step to obtaining preparations from cowslip primrose with a high content of bioactive substances.     

Effect of Freeze-Thaw Cycles on the Oxidation of Protein and Fat and Its Relationship with the Formation of Heterocyclic Aromatic Amines and Advanced Glycation End Products in Raw Meat

The aim of this research was to investigate the effect of the number of freeze–thaw cycles (0, 1, 3, 5, and 7) on porcine longissimus protein and lipid oxidation, as well as changes in heterocyclic aromatic amines (HAAs) and advanced glycation end products (AGEs) and their precursors. We analyzed the relationship among HAAs, AGEs, oxidation, and precursors and found the following results after seven freeze–thaw cycles. The HAAs, Norharman and Harman, were 20.33% and 16.67% higher, respectively. The AGEs, Nε-carboxyethyllysine (CEL) and Nε-carboxymethyllysine (CML), were 11.81% and 14.02% higher, respectively. Glucose, creatine, and creatinine were reduced by 33.92%, 5.93%, and 1.12%, respectively after seven freeze–thaw cycles. Norharman was significantly correlated with thiobarbituric acid reactive substances (TBARS; r² = 0.910) and glucose (r² = −0.914). Harman was significantly correlated to TBARS (r² = 0.951), carbonyl (r² = 0.990), and glucose (r² = −0.920). CEL was correlated to TBARS (r² = 0.992) and carbonyl (r² = 0.933). These changes suggest that oxidation and the Maillard reaction during freeze–thaw cycles promote HAA and AGE production in raw pork.     

LaTiO高k栅介质Ge MOS电容电特性及Ti含量优化

采用共反应溅射法将Ti添加到La_2O_3中,制备了LaTiO/Ge金属-氧化物-半导体电容,并就Ti含量对器件电特性的影响进行了仔细研究.由于Ti-基氧化物具有极高的介电常数,LaTiO栅介质能够获得高k值;然而由于界面/近界面缺陷随着Ti含量的升高而增加,添加Ti使界面质量恶化,进而使栅极漏电流增大、器件可靠性降低.因此,为了在器件电特性之间实现协调,对Ti含量进行优化显得尤为重要.就所研究的Ti/La_2O_3比率而言,18.4%的Ti/La_2O_3比率最合适.该比率导致器件呈现出高k值(22.7)、低D_(it)(5.5×10~(11)eV~(-1)·cm~(-2))、可接受的J_g(V_g=1V,J_g=7.1×10~(-3)A·cm~(-2))和良好的器件可靠性.     

基于RST-QFD-Bayes的新型装甲装备通用质量特性评价指标体系构建研究

针对新型装甲装备通用质量特性评价指标体系难以确定的问题,在明确评价指标体系构建原则的基础上,结合新型装甲装备特点,确定了通用质量特性初始评价指标及指标筛选要求,运用QFD将新型装甲装备通用质量特性需求映射为评价指标筛选要求,采用粗糙集理论(Rough Set Theory,RST)确定了指标筛选重要度,考虑到关联度的不确定性及多个专家估计值的平均值和估计值的波动程度,将贝叶斯理论引入关系矩阵的确定中,用区间数确定了关联度,进行了评价指标筛选,构建了新型装甲装备通用质量特性评价指标体系,为新型装甲装备通用质量特性评价奠定了基础。     

一种牧场配料系统的设计与实现

提出了一种应用于移动Ad Hoc网络的分布式资源接纳控制机制,在目的节点和中间节点部署不同的资源接纳控制模块,能以接近通话或者分组传输的时间间隔适应网络的动态变化,为业务提供较好的QoS保障,并且能够支持多播及接收者异质性。仿真结果表明,添加资源接纳控制机制后,时延、抖动及丢包率分别降低了25.75%,51.76%和24.15%。     

Dynamics and optimal control in a spatially structured economic growth model with pollution diffusion and environmental taxation

In the first part of this paper we present a spatially structured dynamic economic growth model which takes into account the level of pollution and a possible taxation based on the amount of produced pollution. In the second part we analyze an optimal harvesting control problem with an objective function composed of three terms, namely the intertemporal utility of the decision maker, the space–time average of the level of pollution in the habitat, and the disutility due to the imposition of taxation.     

Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.