安吉白茶挥发性成分及关键呈香成分分析

采用搅拌棒吸附萃取结合气相色谱-质谱联用技术研究安吉白茶的挥发性成分组成特点,并利用气相色谱-嗅闻-质谱技术结合相对气味活性值分析了安吉白茶的关键呈香成分。结果表明,在20 个安吉白茶样品中共检测到109 种挥发性成分,其中含量最高的成分有香叶醇、邻苯二甲酸二异丁酯、植醇、水杨酸甲酯、顺式茉莉酮、亚麻酸、芳樟醇等;不同等级安吉白茶的挥发性成分含量存在较大差异;此外,基于34 个共有特征峰,建立安吉白茶挥发性成分指纹图谱;16 种化合物被鉴定为安吉白茶的关键呈香成分,包括反式-β-紫罗兰酮、香叶醇、芳樟醇、己醛、庚醛、(E)-2-庚烯醛、α-紫罗兰酮和(Z)-己酸-3-己烯酯等。     

陈皮生物活性成分及其保健功能研究进展

本研究以陈皮为原料,使用乳酸芽孢杆菌DU-106进行发酵,探讨了发酵陈皮水提取物（Fermented Water Extract, FWE）和未发酵陈皮水提取物（Water Extract, WE）的主要成分、体外抗氧化活性及其对秀丽隐杆线虫抗衰老作用的变化情况。测定两种水提物的总黄酮、总多酚和总糖的含量;采用1,1-二苯基-2-三硝基苯肼（2,2-diphenyl-1-picrylhydrazyl, DPPH）自由基清除率、羟基自由基清除率、亚铁离子螯合率和总还原能力四个指标对比两种水提物的体外抗氧化活性;以低（1 mg/mL）、中（3 mg/mL）、高（5 mg/mL）三个剂量的两种水提物为样品饲喂秀丽隐杆线虫,评价两种水提物的体内抗氧化活性。研究结果表明,FWE的总黄酮含量极显著高于WE组（P<0.01）,达8.42%±0.25%;两种水提物均有一定的体外抗氧化活性,且FWE效果优于WE;线虫实验表明陈皮水提物对线虫生育率无显著影响（P>0.05）,中、高剂量FWE组的抗热应激能力和抗氧化应激能力显著高于WE组（P<0.05）,延长了线虫的最大寿命（P<0.05）,其中氧化应激实验中高剂量组FWE组的最大寿命达（4.30±0.00） h,相比WE组延长了16.22%。此外,FWE组在提升线虫运动能力、体内抗氧化酶活性及降低活性氧、丙二醛水平等方面均优于WE组。综上所述,乳酸芽孢杆菌发酵可提高陈皮水提取物的抗氧化活性及其延长秀丽隐杆线虫寿命的能力。     

Deformation kinetics of commercial Ti-50A (0.5 At. Pct Oeq) at low temperatures (T<0.3T m )

The effects of strain rate and temperature on the flow stress of commercial Ti-50A titanium (0.5 at. pct Oeq) wire of 2 and 22 μm grain size were investigated over the range of 4.2 to 700 K. Employing the thermally activated plastic flow concept, it was concluded that the rate-controlling mechanism in Ti-50A at low temperatures (T<≈600 K) is the thermally activated overcoming of interstitial solute atom obstacles (mainly oxygen) by dislocations moving on the first-order prism planes. The Gibbs free energy of activation for the process is ≈1.5 ev(≈0.2 μb³), the maximum force of interaction ≈8 X 10^-5 dynes (≈0.2 smb²), and the activation distance at which the force first rises rapidly ≈ lb. The derived deformation kinetics parameters are in reasonable accord with the Fleischer-Friedel model of solid solution strengthening, the interaction energy being given by the combined effect of the tetragonal distortion and the modulus mismatch produced by the interstitials. Qualitative accord is also obtained for the breaking of chemical bonds between the interstitial solutes and the surrounding titanium atoms by the passage of dislocations.     

Delineating the construct network of the Personnel Reaction Blank: Associations with externalizing tendencies and normal personality.

Integrity testing has long been utilized in personnel selection to screen for tendencies toward counterproductive workplace behaviors. The construct of externalizing from the psychopathology literature represents a coherent spectrum marked by disinhibitory traits and behaviors. The present study drew on a sample of male and female undergraduates to examine the construct network of the Personnel Reaction Blank (PRB; H. G. Gough, R. D. Arvey, & P. Bradley, 2004), a measure of integrity, in relation to externalizing as well as normal-range personality constructs assessed by the Multidimensional Personality Questionnaire (MPQ; A. Tellegen & N. G. Waller, 2008). Results revealed moderate to strong associations between several PRB scales and externalizing, which were largely accounted for by MPQ traits subsumed by Negative Emotionality and Constraint. After accounting for MPQ traits in the prediction of externalizing, a modest predictive increment was achieved when adding the PRB scales, particularly biographical indicators from the Prosocial Background subscale. The findings highlight externalizing as a focal criterion for scale development in the integrity testing literature and help delineate the construct network of the PRB within the domains of personality and psychopathology. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Graphs for Mining-Based Defect Localization in Multithreaded Programs

Trends in modern multicore architecture design requires software developers to develop and debug multithreaded programs. Consequently, software developers must face new challenges because of bug patterns occurring at runtime and due to the non-deterministic behavior of multi-threaded program executions. This calls for new defect-localization techniques. There has been much work in the field of defect localization for sequential programs on the one side and on the localization of specific multithreading bugs on the other side, but we are not aware of any general technique for multithreaded programs. This paper proposes such an approach. It generalizes data mining-based defect-localization techniques for sequential programs. The techniques work by analyzing call graphs. More specifically, we propose new graph representations of multithreaded program executions as well as two mining-based localization approaches based on these representations. Our evaluation shows that our technique yields good results and is able to find defects that other approaches cannot localize.     

Database‐Assisted Object Retrieval for Real‐Time 3D Reconstruction

In recent years, real‐time 3D scanning technology has developed significantly and is now able to capture large environments with considerable accuracy. Unfortunately, the reconstructed geometry still suffers from incompleteness, due to occlusions and lack of view coverage, resulting in unsatisfactory reconstructions. In order to overcome these fundamental physical limitations, we present a novel reconstruction approach based on retrieving objects from a 3D shape database while scanning an environment in real‐time. With this approach, we are able to replace scanned RGB‐D data with complete, hand‐modeled objects from shape databases. We align and scale retrieved models to the input data to obtain a high‐quality virtual representation of the real‐world environment that is quite faithful to the original geometry. In contrast to previous methods, we are able to retrieve objects in cluttered and noisy scenes even when the database contains only similar models, but no exact matches. In addition, we put a strong focus on object retrieval in an interactive scanning context — our algorithm runs directly on 3D scanning data structures, and is able to query databases of thousands of models in an online fashion during scanning.     

Automatic diagnosis of diabetes using adaptive neuro‐fuzzy inference systems

Abstract: A new approach based on an adaptive neuro‐fuzzy inference system (ANFIS) is presented for diagnosis of diabetes diseases. The Pima Indians diabetes data set contains records of patients with known diagnosis. The ANFIS classifiers learn how to differentiate a new case in the domain by being given a training set of such records. The ANFIS classifier is used to detect diabetes diseases when eight features defining diabetes indications are used as inputs. The proposed ANFIS model combines neural network adaptive capabilities and the fuzzy logic qualitative approach. The conclusions concerning the impacts of features on the diagnosis of diabetes disease are obtained through analysis of the ANFIS. The performance of the ANFIS model is evaluated in terms of training performances and classification accuracies and the results confirm that the proposed ANFIS model has potential in detecting diabetes diseases.