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A number of shortcomings of space syntax—a well-known technique of urban analysis—were recently discussed in the scientific literature. They are mostly traceable to the reliance in space syntax on the 'axial map': a simplified line-of-sight description of the city, which is then analysed based on its topology. This paper explores how another type of urban representations—namely the urban digital elevation model (DEM), a raster map which stores building heights—could prove helpful in providing complementary information to space syntax. Although the use of DEMs is common in the geo-sciences, their application in urban studies is more recent and shows promise. This paper presents several analysis algorithms to derive urban lines of sight, viewsheds, travelling time maps, and simulations based on cellular automata. The relevance of the approach is discussed, suggesting that it could effectively complement traditional space syntax in the coming years.

This paper reports on a number of inconsistencies that appear in space syntax—a well-known technique of urban analysis—when dealing with certain geometrical configurations. At a simple level, the analysis of regularly gridded urban textures (such as Manhattan's) reveals the difficulty of accepting the claim that space syntax allows the modelling of pedestrian choice making. In more complex cases, the distortion of two ideal textures produces a topological discontinuity, leading to the unacceptable situation where one single urban configuration produces two conflicting outcomes when analysed with space syntax tools. Several other points are also discussed, such as the difficulty of space syntax to take into account building height and land use, and its sensitivity to boundary conditions. Conclusions seem to suggest that the topological representation of cities, on which space syntax is based, discards precious metric information and is rather limiting. It is envisaged that with current increases in computational power new algorithms might allow a deeper understanding of urban texture, based on the full exploration of its metric and topological properties. This would contribute to answer the fascinating question which space syntax has helped to frame: what is the influence of urban configuration on social life?

Some questions about space syntax—a well-known technique of urban analysis developed over the past decades by Bill Hillier et al—were raised by Ratti in this journal. Hillier and Penn produced a detailed rejoinder, rebutting most of the criticisms and restating the assumptions made by the technique. However, their arguments, if accepted, lead to paradoxical consequences.

Cover -- Half Title -- Title -- Copyright -- Contents -- PART I: THE CITY OF TOMORROW (AND TODAY) -- 1 Futurecraft -- 2 Bits and Atoms -- 3 Wiki City -- PART II: METROPOLITAN INFORMATION FLOWS -- 4 Big (Urban) Data -- 5 Cyborg Society -- 6 Living Architecture -- PART III: SENSEABLE CITY -- 7 Mobility -- 8 Energy -- 9 Knowledge -- PART IV: LOOKING FORWARD -- 10 Hack the City -- 11 Epilogue -- Notes -- Acknowledgments -- Credits -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- V -- W -- Y -- Z

A new paradigm for investigating the environment consequences of urban texture is proposed. Using raster-based models and software algorithms derived from image processing the authors develop efficient methods of measuring geometric parameters and predicting radiation exchange. The possibilities of generating synthetic urban textures and of integrating cellular automata are explored. Results suggest the possibility of a raster-based urban model to inform planning and design.

The field of Open Source Hardware Mechanical Ventilators (OSH-MVs) has seen a steep rise of contributions during the 2020 COVID-19 pandemic. As predictions showed that the number of patients would exceed current supply of hospital-grade ventilators, a number of formal (academia, the industry and governments) and informal (fablabs and startups) entities raced to develop cheap, easy-to-fabricate mechanical ventilators. The presence of actors with very diverse modus operandi as well as the speed at which the field has grown, led to a fragmented design space characterized by a lack of clear design patterns, projects not meeting the minimum functional requirements or showing little-to-no innovation; but also valid alternatives to hospital-grade devices. In this paper we provide a taxonomic system to help researchers with no background in biomedical engineering to read, understand and contribute to the OSH-MV field. The taxonomy is composed of ten properties that are read through the lenses of three reflection criteria: buildability, adoptability and scalability. We applied the taxonomy to the analysis of seventeen OSH-MV projects, which are representative of the current landscape of possibilities available for COVID-19 patients. We discuss the different design choices adopted by each project highlighting strengths and weaknesses and we suggest possible directions for the development of the OSH-MV field.

Artificial light has transformed urban life, enhancing visibility, aesthetics, and increasing safety in public areas. However, too much unwanted artificial light leads to light pollution, which has a negative effect on public health and urban ecosystems, as well as on the aesthetic and cultural meanings of the night sky. Some of the factors interfering with the estimation of light pollution in cities are urban features, such as the presence of trees, road dimensions, and the physical characteristics of buildings. In this study, we proposed a simplified model for unwanted upward light coming from street luminaires based on a building height model and the publicly accessible Google Street View images. We simulated and analyzed the obstruction effects of different street features on the light pollution caused by the street lighting system in Cambridge, Massachusetts. By providing quantitative information about the connections between the streetscape features and the amount of unwanted upward artificial light, this study provides reference values to inform policies aimed at curbing light pollution.

Quantifying regularities in behavioral dynamics is of crucial interest for understanding collective social events such as panics or political revolutions. With the widespread use of digital communication media it has become possible to study massive data streams of user-created content in which individuals express their sentiments, often towards a specific topic. Here we investigate messages from various online media created in response to major, collectively followed events such as sport tournaments, presidential elections, or a large snow storm. We relate content length and message rate, and find a systematic correlation during events which can be described by a power law relation—the higher the excitation, the shorter the messages. We show that on the one hand this effect can be observed in the behavior of most regular users, and on the other hand is accentuated by the engagement of additional user demographics who only post during phases of high collective activity. Further, we identify the distributions of content lengths as lognormals in line with statistical linguistics, and suggest a phenomenological law for the systematic dependence of the message rate to the lognormal mean parameter. Our measurements have practical implications for the design of micro-blogging and messaging services. In the case of the existing service Twitter, we show that the imposed limit of 140 characters per message currently leads to a substantial fraction of possibly dissatisfying to compose tweets that need to be truncated by their users. ; Ericsson Inc. (''Signature of Humanity'' fellowship)