How student’s personality traits affect Computer Based Assessment Acceptance: Integrating BFI with CBAAM

Researchers in the Information Systems (IS) field have put considerable effort on identifying how personality affects technology acceptance. This study is a further step towards this direction within the context of Computer Based Assessment (CBA). Particularly, it investigates how the five personality factors affect the most important variables regarding CBA’s acceptance. For this purpose, 117 participants were required to complete a survey questionnaire. The questionnaire included the Big Five Inventory (BFI) questions in order to measure the five personality traits, and 23 items regarding student’s perceptions. Partial Least Squares (PLS) was used to test the measurement and the structural model. Results underline that Neuroticism has significant negative effect on Perceived Usefulness and on Goal Expectancy, Agreeableness determines Social Influence and Perceived Ease of Use, Conscientiousness defines Perceived Ease of Use, while Extroversion and Openness explain Perceived Importance. Important implications of these results are discussed.     

The Menpo Benchmark for Multi-pose 2D and 3D Facial Landmark Localisation and Tracking

International Journal of Computer Vision - In this article, we present the Menpo 2D and Menpo 3D benchmarks, two new datasets for multi-pose 2D and 3D facial landmark localisation and tracking. In...     

基于单试验脑电图的n-back任务中的脑力负荷分类

近年来，脑力负荷估计已经经历了广泛的研究，因为监测认知负荷的能力能够防止认知超负荷并且改善工作场所安全。脑电图（EEG）信号已经被发现是一种客观和非侵入性的脑力负荷的测量方式。然而，作为实时脑力负荷监测和脑机接口研究的重要一步，基于单试验EEG数据的认知负荷的评估一直是一个重大的挑战。最近，许多高级的特征提取方法和机器学习算法已经被采用于基于EEG的脑力负荷评估中。在本研究中，使用在具有2个难度水平的n back任务的执行期间记录的EEG数据进行了单试验脑力负荷分类，测试了3种类型的特征提取的有效性（谱功率、离散小波变换和公共空间滤波），并评估了4种分类算法的性能（支持向量机、K 近邻、随机森林和梯度推进分类器）。研究结果表明，公共空间滤波是性能最好的基于单试验的脑力负荷分类的特征提取方法，而且最佳性能可以通过将来自谱功率或离散小波变换的特征与来自公共空间滤波的特征相结合，并采用随机森林分类器来实现。这项研究可能对基于单试验脑电图数据的脑力负荷评估中的特征提取方法以及机器学习算法的选择提供一些有用的指导。     

High throughput cellular biosensor for the ultra-sensitive,ultra-rapid detection of aflatoxin M1

The aim of this study was the development of a rapid novel biosensor system based on the Bioelectric Recognition Assay (BERA) for the detection of aflatoxin M1 (AFM1). Membrane-engineering was achieved by electroinsertion of AFM1-homologous antibodies into the membrane of the cells. The sensor measured the electric response of cultured membrane-engineered fibroblast cells suspended in an alginate gel matrix due to the change of their membrane potential after the interaction of the analyte molecules with the antibodies. The BERA-based sensor was able to detect AFM1 rapidly (3min) at very low concentrations (5 pg/ml = 5 ppt), thus demonstrating a higher sensitivity than most currently available biosensor-based methods. In addition, the assay was quite selective against other aflatoxins, such as aflatoxin B1 and ochratoxin A. Furthermore, the assay system allowed for high throughput AFM1 analysis (160 individual tests/h), due to its multiple cell–electrode interface array. Although further research is required for the optimization of the assay, the elimination of possible matrix effects and its validation by assaying actual food samples, this novel biosensor offers new perspectives for ultra-rapid, ultra-sensitive and low-cost monitoring of mycotoxins in food commodities.     

Alleviation of stuck wine fermentations using salt‐preconditioned yeast

The influence of salt (sodium chloride) on the cell physiology of wine yeast was investigated. Cellular viability and population growth of three wine‐making yeast strains of Saccharomyces cerevisiae, and two non‐Saccharomyces yeast strains associated with wine must microflora (Kluyveromyces thermotolerans and K. marxianus) were evaluated following salt pre‐treatments. Yeast cells growing in glucose defined media exposed to different sodium chloride concentrations (4, 6 and 10% w/v) exhibited enhanced viabilities compared with nontreated cultures in subsequent trial fermentations. Salt ‘preconditioning’ of wine yeast seed cultures was also shown to alleviate stuck and sluggish fermentations at the winery scale, indicating potential benefits for industrial fermentation processes. It is hypothesized that salt induces specific osmostress response genes to enable yeast cells to better tolerate the rigours of fermentation, particularly in high sugar and alcohol concentrations. Copyright © 2014 The Institute of Brewing & Distilling     

Using Real Options Theory to Irrigation Dam Investment Analysis: An Application of Binomial Option Pricing Model

This paper demonstrates the utility of the real options approach to irrigation dam investment analysis. The main objective is to show how to calculate the option values of selected options that may be available to managers of irrigation dam investments. The paper provides an empirical application, which compares an irrigation dam investment using the static Net Present Value (NPV) model and the real options approach and shows how it can be adopted to model uncertainty and managerial flexibility in dam management. Four management options are used for the real options approach: an option to delay the investment, an option to enlarge the dam, an option to abandon the dam, and multiple options that evaluated all three options together. All options were evaluated using the binomial option pricing model, where water values are assumed to follow a multiplicative binomial process. The analysis show that although the traditional NPV approach accepted the investment as profitable the option approach provided better results showing that all three options were highly valuable if exercised. When real options are considered, the traditional NPV model for assessing the profitability of a dam investment may fail to provide an adequate decision-making framework because it does not properly value management’s ability to adjust to shocks in the economy, as well as risks and uncertainty.     

Energy sector pricing: On the role of neglected nonlinearity

Modern economies have been subjected to a number of shocks during the past several years such as the burst of the Internet bubble, terrorist attacks, corporate scandals, the war in Iraq, the uncertainty about energy prices, and the recent subprime mortgage crisis. In particular, during the last few years, the energy shock has caused concerns for potential stagflation for both the United States and numerous other countries. We perform numerous univariate tests for non-linearity and chaotic structure using price data from the energy sector to resolve whether the sector's fundamentals or exogenous shocks drive these prices.