126,436 research outputs found
Electoral competition in a multidimensional political arena - parallel moves instead of convergence in policy platforms
This paper provides a theoretical model of electoral competition in a multidimensional political arena with a heterogenous electorate and politically active interest groups. The emerging pattern of movement in policy platforms is fundamentally different to the concept of convergence proposed by the spatial theory of voting. Rather than the centre of the scale of policy preference, its extreme ends, occupied by dominant-issue-voters and interest groups, attract the policy platforms. The platforms move in parallel instead of towards each other, while the difference in policy platforms is reduced only under certain conditions. --voters,interest groups,ideology,political parties,convergence
Multidimensional Urban Segregation - Toward A Neural Network Measure
We introduce a multidimensional, neural-network approach to reveal and
measure urban segregation phenomena, based on the Self-Organizing Map algorithm
(SOM). The multidimensionality of SOM allows one to apprehend a large number of
variables simultaneously, defined on census or other types of statistical
blocks, and to perform clustering along them. Levels of segregation are then
measured through correlations between distances on the neural network and
distances on the actual geographical map. Further, the stochasticity of SOM
enables one to quantify levels of heterogeneity across census blocks. We
illustrate this new method on data available for the city of Paris.Comment: NCAA S.I. WSOM+ 201
Evidence of the relationship between social vulnerability and the spread of COVID-19 in urban spaces.
Modeling the social-spatial structure of urban spaces can facilitate the development of guidelines aimed at curbing the spread of the COVID-19 pandemic while also acting as an instrument that helps decision-making concerning mitigation policies. The modeling process starts with catego-rization of urban spaces based on the concept of social vulnerability. A model is created based on this concept and the theory of analysis of social areas. Statistical techniques of factor analysis and geostatistics are applied. This generates a map of social differentiation that, when related to data on the evolution of the contagion, generates a multidimensional model of social vulnerability. The application of this model towards people (social structure) and the environment where they live (spatial structure) is specified. Our model assumes the uniqueness of cities, and it is intended to be a broadly applicable model that can be extrapolated to other urban areas if pertinent revisions are made. Our work demonstrates that aspects of the social and urban structures may be validly used to analyze and explain the spatial spread of COVID-19.FEDER-COVID19 (CV20-27760), Regional Government, Spain. This study is part of the project âVulnerability and post-COVID resilience in the metropolitan area of MĂĄlaga (Spain)â. Partial funding for open access charge: University of MĂĄlaga and Consortium of University Libraries of Andalusia (CBUA acronym in Spain)
Operationalizing the circular city model for naples' city-port: A hybrid development strategy
The city-port context involves a decisive reality for the economic development of territories and nations, capable of significantly influencing the conditions of well-being and quality of life, and of making the Circular City Model (CCM) operational, preserving and enhancing seas and marine resources in a sustainable way. This can be achieved through the construction of appropriate production and consumption models, with attention to relations with the urban and territorial system. This paper presents an adaptive decision-making process for Naples (Italy) commercial port's development strategies, aimed at re-establishing a sustainable city-port relationship and making Circular Economy (CE) principles operative. The approach has aimed at implementing a CCM by operationalizing European recommendations provided within both the Sustainable Development Goals (SDGs) framework-specifically focusing on goals 9, 11 and 12-and the Maritime Spatial Planning European Directive 2014/89, to face conflicts about the overlapping areas of the city-port through multidimensional evaluations' principles and tools. In this perspective, a four-step methodological framework has been structured applying a place-based approach with mixed evaluation methods, eliciting soft and hard knowledge domains, which have been expressed and assessed by a core set of Sustainability Indicators (SI), linked to SDGs. The contribution outcomes have been centred on the assessment of three design alternatives for the East Naples port and the development of a hybrid regeneration scenario consistent with CE and sustainability principles. The structured decision-making process has allowed us to test how an adaptive approach can expand the knowledge base underpinning policy design and decisions to achieve better outcomes and cultivate a broad civic and technical engagement, that can enhance the legitimacy and transparency of policies
Perspects in astrophysical databases
Astrophysics has become a domain extremely rich of scientific data. Data
mining tools are needed for information extraction from such large datasets.
This asks for an approach to data management emphasizing the efficiency and
simplicity of data access; efficiency is obtained using multidimensional access
methods and simplicity is achieved by properly handling metadata. Moreover,
clustering and classification techniques on large datasets pose additional
requirements in terms of computation and memory scalability and
interpretability of results. In this study we review some possible solutions
Directed transport as a mechanism for protein folding in vivo
We propose a model for protein folding in vivo based on a Brownian-ratchet
mechanism in the multidimensional energy landscape space. The device is able to
produce directed transport taking advantage of the assumed intrinsic asymmetric
properties of the proteins and employing the consumption of energy provided by
an external source. Through such a directed transport phenomenon, the
polypeptide finds the native state starting from any initial state in the
energy landscape with great efficacy and robustness, even in the presence of
different type of obstacles. This model solves Levinthal's paradox without
requiring biased transition probabilities but at the expense of opening the
system to an external field.Comment: 16 pages, 7 figure
Visualisation techniques for users and designers of layout algorithms
Visualisation systems consisting of a set of components through which data and interaction commands flow have been explored by a number of researchers. Such hybrid and multistage algorithms can be used to reduce overall computation time, and to provide views of the data that show intermediate results and the outputs of complementary algorithms. In this paper we present work on expanding the range and variety of such components, with two new techniques for analysing and controlling the performance of visualisation processes. While the techniques presented are quite different, they are unified within HIVE: a visualisation system based upon a data-flow model and visual programming. Embodied within this system is a framework for weaving together our visualisation components to better afford insight into data and also deepen understanding of the process of the data's visualisation. We describe the new components and offer short case studies of their application. We demonstrate that both analysts and visualisation designers can benefit from a rich set of components and integrated tools for profiling performance
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