Invisible cities: the table of contents and the labyrinths of reality

In Invisible Cities (1972), Italo Calvino contrasts a rigid outline structure with a flexible textual content. The tension comprised by the numerical structure proposed in the table of contents stands out against the set of polissemic texts which make up the subject matter of the book. The opposition between form and content point to a fruitful dichotomy in the conception of the novel linked to the theories of the open and closed work. This essay will investigate the structural construction of Invisible Cities by looking at its table of contents, seeking to discuss some models of formalistic representation proposed by the criticism and the specific contribution they may, or may not, provide. The objective is to analyse the pertinence of such theories in the light of historical and cultural approaches. Aiming to uncover possible meanings which arise from the debate, this essay will question to what extent structural complexities can be considered literary if they are not ultimately related to the culture in which a text is found.

Evaluation of ochratoxin A exposure degree in two Portuguese cities through wheat and maize bread consumption during the winter 2007

The occurrence of OTA in fresh and packed wheat and in maize bread and the evaluation of the exposure degree through their consumption in two Portuguese populations from Porto and Coimbra, during the winter of 2007, were studied. One hundred and sixty eight bread samples, 61 maize and 107 wheat, were analysed by liquid chromatography–fluorescence detection (LC–FD). The results showed that 84% of samples were contaminated, with a maximum level of 3.85 ng/g (above the EU maximum limit, 3 ng/g). Fresh wheat bread presented higher levels than packed wheat bread. Moreover, the traditional maize bread, in either city, was consistently more contaminated than wheat bread, 0.25 vs 0.19 ng/g, and 0.48 vs 0.34 ng/ g for Porto and Coimbra, respectively. Avintes maize bread showed the highest mean contamination and maximum levels. The higher estimated daily intake of OTA from both types of bread in the population of Coimbra compared to Porto reflects the higher average contamination of bread in the first city.

Sensor Integration for Smart Cities Using Multi-Hop Networks

Smart Cities are designed to be living systems and turn urban dwellers life more comfortable and interactive by keeping them aware of what surrounds them, while leaving a greener footprint. The Future Cities Project [1] aims to create infrastructures for research in smart cities including a vehicular network, the BusNet, and an environmental sensor platform, the Urban Sense. Vehicles within the BusNet are equipped with On Board Units (OBUs) that offer free Wi-Fi to passengers and devices near the street. The Urban Sense platform is composed by a set of Data Collection Units (DCUs) that include a set of sensors measuring environmental parameters such as air pollution, meteorology and noise. The Urban Sense platform is expanding and receptive to add new sensors to the platform. The parnership with companies like TNL were made and the need to monitor garbage street containers emerged as air pollution prevention. If refuse collection companies know prior to the refuse collection which route is the best to collect the maximum amount of garbage with the shortest path, they can reduce costs and pollution levels are lower, leaving behind a greener footprint. This dissertation work arises in the need to monitor the garbage street containers and integrate these sensors into an Urban Sense DCU. Due to the remote locations of the garbage street containers, a network extension to the vehicular network had to be created. This dissertation work also focus on the Multi-hop network designed to extend the vehicular network coverage area to the remote garbage street containers. In locations where garbage street containers have access to the vehicular network, Roadside Units (RSUs) or Access Points (APs), the Multi-hop network serves has a redundant path to send the data collected from DCUs to the Urban Sense cloud database. To plan this highly dynamic network, the Wi-Fi Planner Tool was developed. This tool allowed taking measurements on the field that led to an optimized location of the Multi-hop network nodes with the use of radio propagation models. This tool also allowed rendering a temperature-map style overlay for Google Earth [2] application. For the DCU for garbage street containers the parner company provided the access to a HUB (device that communicates with the sensor inside the garbage containers). The Future Cities use the Raspberry pi as a platform for the DCUs. To collect the data from the HUB a RS485 to RS232 converter was used at the physical level and the Modbus protocol at the application level. To determine the location and status of the vehicles whinin the vehicular network a TCP Server was developed. This application was developed for the OBUs providing the vehicle Global Positioning System (GPS) location as well as information of when the vehicle is stopped, moving, on idle or even its slope. To implement the Multi-hop network on the field some scripts were developed such as pingLED and “shark”. These scripts helped upon node deployment on the field as well as to perform all the tests on the network. Two setups were implemented on the field, an urban setup was implemented for a Multi-hop network coverage survey and a sub-urban setup was implemented to test the Multi-hop network routing protocols, Optimized Link State Routing Protocol (OLSR) and Babel.

Building Smarter Cities through Social Entrepreneurship

The objective of the present study is to examine the extent to which social ventures are able to increase the smartness of the cities. To achieve this goal, we adopt a qualitative approach, based on the case study method to obtain valuable insights about different characteristics and strategies of Cais (a non-profit association dedicated to help disadvantaged people in urban areas). By focusing on the analysis of the Cais activities, we assess whether its social intervention match the dimensions proposed by Giffinger et al. (2007) to rank smart cities��� performance, namely if it has smart: (i) economy; (ii) people; (iii) governance; (iv) mobility; (v) environment; and (vi) living. The research shows that the action pursued comprises elements from all the above mentioned dimensions. Further, the analysis reveals that Cais reinforces the smartness of the city where it acts (attributes such as living, economy, people, and environment).