Cyanogenic,carotenoids and protein composition in leaves and roots across seven diverse population found in the world cassava germplasm collection at CIAT,Colombia

The objective of this study was to characterise the nutritional potential of leaves and identify a diversity centre with low cyanide and high nutrient content among 178 Latin American cassava genotypes. This field-based collection represents the seven diversity centres, held at The International Center for Tropical Agriculture (CIAT Palmira, Colombia) by the Cassava Program. The cyanide, all-trans-β-carotene and lutein concentrations in cassava leaves ranged from 346 to 7484 ppm dry basis (db), from 174–547 μg g⁻¹ db and 15–181 μg g⁻¹ db, respectively. Cassava leaves also showed significant levels of essential amino acids leucine, lysine, phenylalanine, valine and threonine, and average total protein content of 26.24 g 100 g⁻¹ db. Among seven diversity centres, South American rainforest group showed low cyanide and high carotene content in leaves. In addition, VEN77 and PAN51 genotypes stood out for having low cyanide in leaves and roots and high carotene in leaves. This genetic diversity can be used to select high potential progenitors for breeding purposes.     

The use of bio-diesel based additive as rheology improver and pour point depressant of Nigerian waxy crude

The chemical method has proved to be the most effective mitigating method of wax deposition in petroleum system as it deals with the root cause of wax formation. Most of the commercial chemicals in the industry are very expensive and toxic. This paper aims the use of biodiesel based additives for improving the rheological behavior and pour points of waxy crude from Nigeria field. The biodiesels derived additives gave better performance than the commercial chemical and the seed oils as greatly improvement in rheology and pour point values of the waxy crude were observed     

Benchmark value determination of energy efficiency indexes for coal-fired power units based on data mining methods

The operational optimisation of coal-fired power units is important for saving energy and reducing losses in the electric power industry. One of the key issues is how to determine the benchmark values of the energy efficiency indexes of the units. Therefore, a new framework for determining these benchmark values is proposed, based on data mining methods. First, the energy efficiency key performance indicators (KPIs) associated with the net coal consumption rate (NCCR) were selected based on the domain knowledge. Second, the decision-making samples with minimal NCCR were acquired with the fuzzy C-means (FCM) clustering algorithm, and the corresponding clustering centres were employed as the benchmark values. Finally, based on the support vector regression (SVR) algorithm, the target values of the NCCR were obtained with the KPIs as input, and the energy saving potential was evaluated by comparing the target values with the historical values of the NCCR. An actual on-duty 1000 MW unit was taken as study unit, and the results show that the energy saving potential is remarkable when the operators adjust the KPIs based on the calculated benchmark values.     

Levelized cost of energy definition – An economic paradox

Using mean value theorem for integrals we show that the well-known LCOE definition is incorrect.     

Attitude-behaviour dissonance regarding the importance of food preservation for customers

The aim of the study was to identify the importance of individual food product attributes (the use of preservatives, processing method, shelf-life period and nutritional value) as well as their relation to the purchase behaviour. To achieve this, consumer preferences were decomposed in conditions of full access to information, and data was compared with actual consumer behaviour related to making purchasing decisions in front of the store shelf. Based on data from 338 respondents, conjoint analysis and repeated ANOVA measurements were carried out, allowing to eliminate individual behavioural patterns. The results showed a dissonance between the consumers attitudes towards the attributes and their shopping behaviour. The processing method was the most important declared attribute for consumers, meanwhile this information was the least searched for during purchase. At the same time, shelf-life period marked as the least important was the main information searched for by consumers when shopping. The results also show a clear dislike towards the use of microwaves as a preservation method, while traditional thermal preservation was marked as the most positive for consumers. In addition, consumers were classified into 3 heterogeneous groups, identifying differences in the preferences of food attributes. The obtained results have practical value relating not only to the preferences of individual attributes, but also to their various variants. The results can be a guide for companies to properly label food products. The indicated dissonance illustrates the educational gap and related insufficient motivation to get to know the product before buying it. This is extremely important in connection with technological development and new food processing methods.     

DP980+Z烘烤硬化值与退火温度的关系

摘要：为了研究退火温度对镀锌DP980+Z烘烤硬化值的影响，退火温度控制在760～820℃之间，系统分析退火温度对烘烤硬化值的影响。通过准静态拉伸试验机测量烘烤硬化值及抗拉强度，采用lepara试剂对组织中的马氏体进行着色，利用金相显微镜及图像处理软件测量马氏体的体积分数；采用扫描电镜观察DP980+Z的双相组织特点，并且将组织图片通过CAD转化成有限元图进行网格划分，建立代表性体积单元（RVE），通过有限元分析铁素体、马氏体强度对烘烤硬化值的影响。在同样的变形量情况下，DP980+Z的原始屈服强度越高，烘烤硬化值越高。     

一种军棋机器博弈的多棋子协同博弈方法

针对在军棋博弈不完全信息对弈中，面对棋子不同价值、不同位置、不同搭配所产生的不同棋力，传统的单子意图搜索算法，不能满足棋子之间的协同性与沟通性，同时也缺乏对敌方的引诱与欺骗等高级对抗能力。本文提出一种结合UCT搜索策略的高价值棋子博弈方法，实现高价值棋子协同博弈的策略。实战经验表明:高价值多棋子军棋协同博弈策略优于单棋子军棋博弈策略。     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

基于承包商预期收益不变的不平衡报价模型

在招标实践中,通常采用最低价中标原则,使得投标人不得不压低其投标价格。基于承包商预期收益不变的不平衡报价模型,是在“工程量清单报价”的条件下,考虑到施工中工程量的变化及施工顺序的影响,体现了资金的时间价值,在保持承包商预期收益不变的前提下,通过调整各分项工程的单价,来降低工程报价,以增加中标机会而建立的。所建立的模型简单,易于操作,并配以具体的工程实例,通过计算机求得其最优解,可供承包商投标报价时参考。     

关于中值定理的几点应用

本文作者给出了在两种不同类型的证明题中应用中值定理的方法.这些方法简单、实用.