Effects of genotype and treatment on the antioxidant activity of sweet potato in Taiwan

Six genotypes of sweet potato commercially available in Taiwan, including TNG57, TNG66, TNG68, TYY1, RP and WP, were used as samples in this study of the effects of steaming and kneading with pre-steaming treatments on the antioxidant components and antioxidant properties of methanolic extracts. Steam treatment increased the total phenols contents of all genotypes (2–13 times), flavonoids content of RP (1.3 times) and anthocyanins contents of RP and WP (5–6 times). Steam treatment also increased the reducing power and scavenging DPPH radical effect of sweet potato flours. For the methanolic extracts of steamed and kneaded flours, reducing powers were 0.02–1.70 at 5.0 mg ml⁻¹ and the scavenging effects on DPPH radicals were 19–92% at 2.5 mg ml⁻¹. Both showed the order of RP > WP > TYY1 and TNG66 > TNG57 and TNG68. However, the chelating effect of the six genotypes at 1.0 mg ml⁻¹ ranged from 50% to 73%. Contents of total phenols, flavonoids, and anthocyanins of sweet potato flours were significantly positively correlated with the reducing power and scavenging DPPH radical effects. After steaming and kneading treatments, RP showed the highest increase in the contents of total phenols, flavonoids and anthocyanins among the six genotypes studied.     

Oxygen absorption kinetics in YBa2Cu3Ox

The oxygen absorption process in highly aligned YBa₂Cu₃O_x samples in air and in pure oxygen was studied at several constant temperatures. The process can be expressed in two steps, a chemical reaction controlled step and a diffusion controlled step. The kinetic equations are as follows respectively:

(1 − a_t) ln(1 − a_t) + a_t = k_Dt

The activation energy was calculated using an Arrhenius equation. The technical conditions of heat treatment for oxygen absorption of highly aligned YBa₂Cu₃O_x crystals are discussed.     

A study on the anodic protection of Titanium evaporators in Al2(SO4)3 solution

The feasibility of the anodic protection of titanium evaporators in Al₂(SO₄)₃ solution was studied by the measurement of polarization curves, weight loss, solubility of passive film and AC impedance. The protection parameters and efficiency were determined. In addition, the practical technology of anodic protection was studied by screening reference electrodes and auxiliary cathodes. Throwing power was also measured. Four rows of tube-type evaporators of titanium have been anodically protected in situ. Field tests lasting more than one year show satisfactory results.     

COIL中BHP浓度对发生O_2(~1△)的影响

本文实验研究了BHP的浓度对产生O2（1△）的影响。实验结果表明：当BHP浓度大于3.5M时，Cl2利用率以及O2（1△）的产率将不依赖于BHP浓度的变化而变化，同时，实验结果表明，使用低浓度的BHP对COIL的操作是可行的。     

fMRI-based Decoding of Visual Information from Human Brain Activity: A Brief Review

Machine Intelligence Research - One of the most significant challenges in the neuroscience community is to understand how the human brain works. Recent progress in neuroimaging techniques have...     

Accelerated electrospark deposition and the wear behavior of coatings

Electrospark deposition (ESD) is a coating process that is featured by low heat input to the substrate. Low coating efficiency and other limitations influence its wider application. The present paper introduces newly designed ESD equipment, by which a higher coating rate can be reached. The relationship among coating thickness, surface roughness, and process parameters such as pulse energy, pulse frequency, and deposition time are presented. Electrospark deposition coating by the new equipment on AISI 1045 steel (with WC-8% Co as electrode) increases the wear resistance by 5 to 8 times. The micromechanism is investigated by scanning electron microscopy observation.     

Joint Classification and Regression for Visual Tracking with Fully Convolutional Siamese Networks

International Journal of Computer Vision - Visual tracking of generic objects is one of the fundamental but challenging problems in computer vision. Here, we propose a novel fully convolutional...     

二溴对甲基偶氮甲磺光度法测定钢中微量锶

研究了二溴对甲基偶氮甲磺与锶生成2:1兰色络合物进行钢中微量锶的测定.该法λ_(max)=638nm,摩尔吸光系数E_(638)=5.01×10~4,锶量在0.02～0.34μg/L范围内服从比尔定律.方法已用于钢中微量锶的测定,结果满意.     

Predicting dam failure risk for sustainable flood retention basins: A generic case study for the wider Greater Manchester area

This study aims to provide a rapid screening tool for assessment of sustainable flood retention basins (SFRBs) to predict corresponding dam failure risks. A rapid expert-based assessment method for dam failure of SFRB supported by an artificial neural network (ANN) model has been presented. Flood storage was assessed for 110 SFRB and the corresponding Dam Failure Risk was evaluated for all dams across the wider Greater Manchester study area. The results show that Dam Failure Risk can be estimated by using the variables Dam Height, Dam Length, Maximum Flood Water Volume, Flood Water Surface Area, Mean Annual Rainfall (based on Met Office data), Altitude, Catchment Size, Urban Catchment Proportion, Forest Catchment Proportion and Managed Maximum Flood Water Volume. A cross-validation R² value of 0.70 for the ANN model signifies that the tool is likely to predict variables well for new data sets. Traditionally, dams are considered safe because they have been built according to high technical standards. However, many dams that were constructed decades ago do not meet the current state-of-the-art dam design guidelines. Spatial distribution maps show that dam failure risks of SFRB located near cities are higher than those situated in rural locations. The proposed tool could be used as an early warning system in times of heavy rainfall.     

Least squares recursive projection twin support vector machine for classification

In this paper we formulate a least squares version of the recently proposed projection twin support vector machine (PTSVM) for binary classification. This formulation leads to extremely simple and fast algorithm, called least squares projection twin support vector machine (LSPTSVM) for generating binary classifiers. Different from PTSVM, we add a regularization term, ensuring the optimization problems in our LSPTSVM are positive definite and resulting better generalization ability. Instead of usually solving two dual problems, we solve two modified primal problems by solving two systems of linear equations whereas PTSVM need to solve two quadratic programming problems along with two systems of linear equations. Our experiments on publicly available datasets indicate that our LSPTSVM has comparable classification accuracy to that of PTSVM but with remarkably less computational time.