Automated highway systems and hard-shoulders running: A case study

The purpose of this research was to evaluate the increase of capacity of existing motorway resulting from the implementation of relatively new traffic control strategies, as the automated highway systems (AHS) and the hard-shoulder running (HSR). Was examined the Italian motorway A22, belonging to Trans-European Road Network, corridor Helsinki - La Valletta. Many traffic surveys were done (year 2014) in several road sections. For each of them have been carried out the flow diagrams, the traffic flow parameters (capacity C, free flow speed vf,jam density kjam) and the relationship between flow rate of lane (right lane Qright and passing lane Qpass) and total flow rate Qt. The current carriageway capacities are in the range 2.703 veh/h \uf7 3.621 veh/h. To improve the capacity, a hard-shoulder running is planned, in both directions of the A22, for a total length of 128 km. This type of traffic control strategy allows an increase of the capacity up to 35%. Instead, for the hypothesized safety conditions of the platooned automated vehicles, a single lane with an AHS gives rise to a capacity of about 5.500 veh/h (reaction time \u3b4= 0, 1 s)

Electrosynthesized poly(o-aminophenol) films as biomimetic coatings for dopamine detection on Pt substrates

Dopamine (DA) is a neurotransmitter, and its levels in the human body are associated with serious diseases. The need for a suitable detection method in medical practice has encouraged the development of electrochemical sensors that take advantage of DA electroactivity. Molecularly imprinted polymers (MIPs) are biomimetic materials able to selectively recognize target analytes. A novel MIP sensor for DA is proposed here based on a thin film of poly(o-aminophenol) electrosynthesized on bare Pt. A fast and easy method for executing the procedure for MIP deposition has been developed based on mild experimental conditions that are able to prevent electrode fouling from DA oxidation products. The MIP exhibited a limit of detection of 0.65 µM, and appreciable reproducibility and stability. The high recognition capability of poly(o-aminophenol) towards DA allowed for the achievement of notable selectivity: ascorbic acid, uric acid, serotonin, and tyramine did not interfere with DA detection, even at higher concentrations. The proposed sensor was successfully applied for DA detection in urine samples, showing good recovery

Road Design Criteria and Capacity Estimation Based on Autonomous Vehicles Performances. First Results from the European C-Roads Platform and A22 Motorway

Several European road operators and authorities joined the C-Roads Platform with the aim of harmonising the deployment activities of cooperative intelligent transport systems (C-ITS). C-ITS research is preliminary to future automated-driving vehicles. The current conventional highways were designed on traditional criteria and models specifically developed for traffic flows of manually guided vehicles. Thus, this article describes some new criteria for designing and monitoring road infrastructures on the basis of performance features of autonomous (or self-driving) vehicles.The new criteria have been adopted to perform an accurate conformity control of the A22 Brenner motorway, included in the C-Roads Platform, and also to ascertain whether in future it may be travelled by automated vehicles in safety conditions. Always in accordance with the technical and scientific insights required by the C-Roads Platform, a traffic model has been implemented to estimate how the A22 capacity increases compared to current values, by taking various percentages of automated or manual vehicles into consideration. The results given by theoretical models indicate that the highway will be able to be travelled by automated vehicles in safety conditions. On the other hand, the lane capacity is due to increase up to 2.5 times more than the current capacities, experimentally determined through traffic data collected from 4 highway sections by means of Drake's flow model

Reward-sensitive women overeat in a varied food environment, but only when hungry

In the current study we tried to elucidate the relationship between a personality trait, reward sensitivity, and an environmental variable; food variety. Based on scarce previous research we predicted that reward sensitivity would interact with variety in the food environment so that especially high reward sensitive individuals would be vulnerable to overeating in a varied food environment. It turned out that especially the high reward individuals did indeed overeat in a varied food environment. However, this was only the case for the highly reward sensitive individuals who experienced feelings of hunger. In other words, reward sensitivity does not affect food intake in varied food environments as long as feelings of hunger are not present. Future research should concentrate on identifying other factors that interact with the person and the environment to discourage reward-related overeating

Specificity of the failure to inhibit responses in overweight children

Poor response inhibition has been associated with obesity, excessive food intake, and other consumptive behaviours, including alcohol use. However, the correlation between obesity and addictive behaviours like alcoholism is low: people who are obese appear to have a specific problem in restraining food intake. This would imply that obese people have more difficulties in inhibiting responses towards food, compared to other rewarding stimuli. In the present study eighty-nine children (ages 7-9) were tested with the stop signal task, in which responses towards food pictures or toy pictures had to be inhibited. Results showed that children were less effective in inhibiting responses towards food and percentage overweight predicted a lower ability to inhibit responses in general. When dichotomizing the sample in overweight and lean children, it appeared that overweight children were specifically less effective in inhibition towards food cues, compared to lean children. In conclusion: The results confirm weight related inhibitory problems and might explain the increased overeating to food cues in overweight children, as reported in the literature

Exact Distributed Load Centrality Computation: Algorithms, Convergence, and Applications to Distance Vector Routing

Many optimization techniques for networking protocols take advantage of topological information to improve performance. Often, the topological information at the core of these techniques is a centrality metric such as the Betweenness Centrality (BC) index. BC is, in fact, a centrality metric with many well-known successful applications documented in the literature, from resource allocation to routing. To compute BC, however, each node must run a centralized algorithm and needs to have the global topological knowledge; such requirements limit the feasibility of optimization procedures based on BC. To overcome restrictions of this kind, we present a novel distributed algorithm that requires only local information to compute an alternative similar metric, called Load Centrality (LC). We present the new algorithm together with a proof of its convergence and the analysis of its time complexity. The proposed algorithm is general enough to be integrated with any distance vector (DV) routing protocol. In support of this claim, we provide an implementation on top of Babel, a real-world DV protocol. We use this implementation in an emulation framework to show how LC can be exploited to reduce Babel's convergence time upon node failure, without increasing control overhead. As a key step towards the adoption of centrality-based optimization for routing, we study how the algorithm can be incrementally introduced in a network running a DV routing protocol. We show that even when only a small fraction of nodes participate in the protocol, the algorithm accurately ranks nodes according to their centrality

Trends in bone metastasis modeling

Bone is one of the most common sites for cancer metastasis. Bone tissue is composed by different kinds of cells that coexist in a coordinated balance. Due to the complexity of bone, it is impossible to capture the intricate interactions between cells under either physiological or pathological conditions. Hence, a variety of in vivo and in vitro approaches have been developed. Various models of tumor\u2013bone diseases are routinely used to provide valuable information on the relationship between metastatic cancer cells and the bone tissue. Ideally, when modeling the metastasis of human cancers to bone, models would replicate the intra-tumor heterogeneity, as well as the genetic and phenotypic changes that occur with human cancers; such models would be scalable and reproducible to allow high-throughput investigation. Despite the continuous progress, there is still a lack of solid, amenable, and affordable models that are able to fully recapitulate the biological processes happening in vivo, permitting a correct interpretation of results. In the last decades, researchers have demonstrated that three-dimensional (3D) methods could be an innovative approach that lies between bi-dimensional (2D) models and animal models. Scientific evidence supports that the tumor microenvironment can be better reproduced in a 3D system than a 2D cell culture, and the 3D systems can be scaled up for drug screening in the same way as the 2D systems thanks to the current technologies developed. However, 3D models cannot completely recapitulate the inter-and intra-tumor heterogeneity found in patients. In contrast, ex vivo cultures of fragments of bone preserve key cell\u2013cell and cell\u2013matrix interactions and allow the study of bone cells in their natural 3D environment. Moreover, ex vivo bone organ cultures could be a better model to resemble the human pathogenic metastasis condition and useful tools to predict in vivo response to therapies. The aim of our review is to provide an overview of the current trends in bone metastasis modeling. By showing the existing in vitro and ex vivo systems, we aspire to contribute to broaden the knowledge on bone metastasis models and make these tools more appealing for further translational studies