Lowering blood alcohol content levels to save lives: A European case study

Road safety has become an increasing concern in developed countries due to the significant amount of fatalities and the associated economic losses. Only in 2005 these losses rose to 200,000 million euros, a considerable sum ¿ approximately 2% of GDP ¿ that easily justifies any public intervention. One measure taken by governments to address this issue is to enact stricter policies and regulations. Since drunk driving is one of the greatest concerns among public authorities in this field, several European countries have lowered their illegal Blood Alcohol Content (BAC) levels to 0.5 mg/ml during the last decade. This study is the first evaluation of the effectiveness of this transition using European panel-based data (CARE) for the period 1991-2003 with the differences-in-differences method in a fixed effects estimation that allows for any pattern of correlation (Cluster-Robust). The results reveal a positive impact on certain groups of road users and on the whole population when the policy is accompanied by enforcement interventions. Moreover, positive results appeared after a time lag of over two years. Finally, I state the importance of controlling for serial correlation in the evaluation of this type of policy.

Lowering blood alcohol content levels to save lives: A European case study

Road safety has become an increasing concern in developed countries due to the significant amount of fatalities and the associated economic losses. Only in 2005 these losses rose to 200,000 million euros, a considerable sum ¿ approximately 2% of GDP ¿ that easily justifies any public intervention. One measure taken by governments to address this issue is to enact stricter policies and regulations. Since drunk driving is one of the greatest concerns among public authorities in this field, several European countries have lowered their illegal Blood Alcohol Content (BAC) levels to 0.5 mg/ml during the last decade. This study is the first evaluation of the effectiveness of this transition using European panel-based data (CARE) for the period 1991-2003 with the differences-in-differences method in a fixed effects estimation that allows for any pattern of correlation (Cluster-Robust). The results reveal a positive impact on certain groups of road users and on the whole population when the policy is accompanied by enforcement interventions. Moreover, positive results appeared after a time lag of over two years. Finally, I state the importance of controlling for serial correlation in the evaluation of this type of policy.

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Individual Differences in True and False Memory Retrieval Are Related to White Matter Brain Microstructure

We sometimes vividly remember things that did not happen, a phenomenon with general relevance, not only in the courtroom. It is unclear to what extent individual differences in false memories are driven by anatomical differences in memory-relevant brain regions. Here we show in humans that microstructural properties of different white matter tracts as quantified using diffusion tensor imaging are strongly correlated with true and false memory retrieval. To investigate these hypotheses, we tested a large group of participants in a version of the Deese-Roediger-McDermott paradigm (recall and recognition) and subsequently obtained diffusion tensor images. A voxel-based whole-brain level linear regression analysis was performedto relatefractional anisotropyto indices oftrue andfalse memory recall and recognition. True memory was correlated to diffusion anisotropy in the inferior longitudinal fascicle, the major connective pathway of the medial temporal lobe, whereas a greater proneness to retrieve false items was related to the superior longitudinal fascicle connecting frontoparietal structures. Our results show that individual differences in white matter microstructure underlie true and false memory performance.

Fair value versus historical cost-based valuation for biological assets: Predictability of financial information

There is an intense debate on the convenience of moving from historical cost (HC) toward the fair value (FV) principle. The debate and academic research is usually concerned with financial instruments, but the IAS 41 requirement of fair valuation for biological assets brings it into the agricultural domain. This paper performs an empirical study with a sample of Spanish farms valuing biological assets at HC and a sample applying FV, finding no significant differences between both valuation methods to assess future cash flows. However, most tests reveal more predictive power of future earnings under fair valuation of biological assets, which is not explained by differences in volatility of earnings and profitability. The study also evidences the existence of flawed HC accounting practices for biological assets in agriculture, which suggests scarce information content of this valuation method in the predominant small business units existing in the agricultural sector in advanced Western countries

High-Performance-Tensile-Strength Alpha-Grass Reinforced Starch-Based Fully Biodegradable Composites

Though there has been a great deal of work concerning the development of natural fibers in reinforced starch-based composites, there is still more to be done. In general, cellulose fibers have lower strength than glass fibers; however, their specific strength is not far from that of fiberglass. In this work, alpha-fibers were obtained from alpha-grass through a mild cooking process. The fibers were used to reinforce a starch-based biopolymer. Composites including 5 to 35% (w/w) alpha-grass fibers in their formulation were prepared, tested, and subsequently compared with those of wood- and fiberglass-reinforced polypropylene (PP). The term “high-performance” refers to the tensile strength of the studied composites and is mainly due to a good interphase, a good dispersion of the fibers inside the matrix, and a good aspect ratio. The tensile strength of the composites showed a linear evolution for fiber contents up to 35% (w/w). The strain at break of the composites decreased with the fiber content and showed the stiffening effects of the reinforcement. The prepared composites showed high mechanical properties, even approaching those of glass fiber reinforced composites

Improved Privacy-Preserving P2P Multimedia Distribution Based on Recombined Fingerprints

Peer-reviewed

Secure and Anonymous Multimedia Content Distribution in Peer-to-Peer Networks

Peer-reviewed