An adaptive freeway traffic state estimator

Real-data testing results of a real-time nonlinear freeway traffic state estimator are presented with a particular focus on its adaptive features. The pursued general approach to the real-time adaptive estimation of complete traffic state in freeway stretches or networks is based on stochastic nonlinear macroscopic traffic flow modeling and extended Kalman filtering. One major innovative aspect of the estimator is the real-time joint estimation of traffic flow variables (flows, mean speeds, and densities) and some important model parameters (free speed, critical density, and capacity), which leads to four significant features of the traffic state estimator: (i) avoidance of prior model calibration; (ii) automatic adaptation to changing external conditions (e.g. weather and lighting conditions, traffic composition, control measures); (iii) enabling of incident alarms; (iv) enabling of detector fault alarms. The purpose of the reported real-data testing is, first, to demonstrate feature (i) by investigating some basic properties of the estimator and, second, to explore some adaptive capabilities of the estimator that enable features (ii)-(iv). The achieved testing results are quite satisfactory and promising for further work and field applications.     

Méthode simple de résolution des équations intégrais décrivant les courbes de la voltampérométrie cyclique ou triangulaire

Sans résumé     

Consumer perception and use of iron fortified foods is associated with their knowledge and understanding of nutritional issues

Aim

We hypothesised that consumer perception on iron fortified foods and consequent introduction of such products to their diets may depend on their knowledge and understanding on nutritional issues, particularly in relation to iron.

Methods

500 men and women (age 30 ± 12 years) from Athens, Xylokastro, in South Greece and Lamia, in Central Greece participated to the study. Participants were asked about their knowledge in nutritional issues using 28 true/false/do not know questions. These “overall nutrition knowledge” questions were grouped as “general nutrition knowledge” and “iron nutrition knowledge” questions. Answers scored 1, −1 or 0 when correct, wrong or “do not know” respectively. Thus, three different scores were produced, specifically the “overall nutrition knowledge” score, ranging from −28 to 28 and from this, the “general nutrition knowledge” score, ranging from −10 to 10, and the “iron nutrition knowledge” score, ranging from −18 to 18. Perception and consumption of iron fortified products were evaluated and associated with the scores.

Results

Unadjusted logistic regression analysis revealed that one point increase of overall nutrition knowledge score was associated with 4.3% higher likelihood that the consumer believes that iron fortified foods have a positive role in diet (OR = 1.043, 90% CI 1.040-1.080). One point increase of iron nutrition knowledge score was associated with 20% higher likelihood of consuming iron fortified foods more often (OR = 1.200, 90% CI 1.074-1.340).

Conclusions

Consumer perception on iron fortified foods seems to be associated with nutrition knowledge and highlight the importance of focused nutrition education in consumer informed choices.     

European residential buildings and empirical assessment of the Hellenic building stock,energy consumption,emissions and potential energy savings

The existing building stock in European countries accounts for over 40% of final energy consumption in the European Union (EU) member states, of which residential use represents 63% of total energy consumption in the buildings sector. Consequently, an increase of building energy performance can constitute an important instrument in the efforts to alleviate the EU energy import dependency (currently at about 48%) and comply with the Kyoto Protocol to reduce carbon dioxide emissions. This is also in accordance to the European Directive (EPBD 2002/91/EC) on the energy performance of buildings, which is currently under consideration in all EU member states. This paper presents an overview of the EU residential building stock and focuses on the Hellenic buildings. It elaborates the methodology used to determine the priorities for energy conservation measures (ECMs) in Hellenic residential buildings to reduce the environmental impact from CO₂ emissions, through the implementation of a realistic and effective national action plan. A major obstacle that had to overcome was the need to make suitable assumptions for missing detailed primary data. Accordingly, a qualitative and quantitative assessment of scattered national data resulted to a realistic assessment of the existing residential building stock and energy consumption. This is the first time that this kind of aggregate data is presented on a national level. Different energy conservation scenarios and their impact on the reduction of CO₂ emissions were evaluated. Accordingly, the most effective ECMs are the insulation of external walls (33–60% energy savings), weather proofing of openings (16–21%), the installation of double-glazed windows (14–20%), the regular maintenance of central heating boilers (10–12%), and the installation of solar collectors for sanitary hot water production (50–80%).     

Regioselective acylation of flavonoids catalyzed by lipase in low toxicity media

Flavonoid fatty esters were prepared by acylation of flavonoids (rutin and naringin) by fatty acids (C8, C10, C12), catalyzed by immobilized lipase from Candida antarctica in various solvent systems. The reaction parameters affecting the conversion of the enzymatic process, such as the nature of the organic solvent and acyl donor used, the water activity (a_w) of the system, as well as the acyl donor concentration have been investigated. At optimum reaction conditions, the conversion of flavonoids was 50—60% in tert‐butanol at a_w less than 0.11. In all cases studied, only flavonoid monoester was identified, which indicates that this lipase‐catalyzed esterification is regioselective.     

The σ-hole phenomenon of halogen atoms forms the structural basis of the strong inhibitory potency of C5 halogen substituted glucopyranosyl nucleosides towards glycogen phosphorylase b

C5 halogen substituted glucopyranosyl nucleosides (1-(β-D-glucopyranosyl)-5-X-uracil; X=Cl, Br, I) have been discovered as some of the most potent active site inhibitors of glycogen phosphorylase (GP), with respective K(i) values of 1.02, 3.27, and 1.94 μM. The ability of the halogen atom to form intermolecular electrostatic interactions through the σ-hole phenomenon rather than through steric effects alone forms the structural basis of their improved inhibitory potential relative to the unsubstituted 1-(β-D-glucopyranosyl)uracil (K(i) =12.39 μM), as revealed by X-ray crystallography and modeling calculations exploiting quantum mechanics methods. Good agreement was obtained between kinetics results and relative binding affinities calculated by QM/MM-PBSA methodology for various substitutions at C5. Ex vivo experiments demonstrated that the most potent derivative (X=Cl) toward purified GP has no cytotoxicity and moderate inhibitory potency at the cellular level. In accordance, ADMET property predictions were performed, and suggest decreased polar surface areas as a potential means of improving activity in the cell.     

Evaluating the Information Behaviour methods: Formative evaluations of two methods for assessing the functionality and usability of electronic information resources

The importance of user-centred evaluation is stressed by HCI academics and practitioners alike. However, there have been few recent evaluation studies of User Evaluation Methods (UEMs), especially those with the aim of improving methods rather than assessing their efficacy (i.e. formative rather than summative evaluations). In this article, we present formative evaluations of two new methods for assessing the functionality and usability of a particular type of interactive system—electronic information resources. These serve as an example of an evaluation approach for assessing the success of new HCI methods. We taught the methods to a group of electronic resource developers and collected a mixture of focus group, method usage and summary questionnaire data—all focusing on how useful, usable and learnable the developers perceived the methods to be and how likely they were to use them in the future. Findings related to both methods were generally positive, and useful suggestions for improvement were made. Our evaluation sessions also highlighted a number of trade-offs for the development of UEMs and general lessons learned, which we discuss in order to inform the future development and evaluation of HCI methods.     

Decoding stimulus-related information from single-trial EEG responses based on voltage topographies

Neuroimaging studies typically compare experimental conditions using average brain responses, thereby overlooking the stimulus-related information conveyed by distributed spatio-temporal patterns of single-trial responses. Here, we take advantage of this rich information at a single-trial level to decode stimulus-related signals in two event-related potential (ERP) studies. Our method models the statistical distribution of the voltage topographies with a Gaussian Mixture Model (GMM), which reduces the dataset to a number of representative voltage topographies. The degree of presence of these topographies across trials at specific latencies is then used to classify experimental conditions. We tested the algorithm using a cross-validation procedure in two independent EEG datasets. In the first ERP study, we classified left- versus right-hemifield checkerboard stimuli for upper and lower visual hemifields. In a second ERP study, when functional differences cannot be assumed, we classified initial versus repeated presentations of visual objects. With minimal a priori information, the GMM model provides neurophysiologically interpretable features – vis à vis voltage topographies – as well as dynamic information about brain function. This method can in principle be applied to any ERP dataset testing the functional relevance of specific time periods for stimulus processing, the predictability of subject's behavior and cognitive states, and the discrimination between healthy and clinical populations.