Social innovation in urban spaces

Recent international policy advocating for social innovation to be part of strategies to promote sustainable urban development has energised this emerging body of literature. However, there is a need for more sector-specific research to integrate findings on the spatiality of social innovation, co-operative processes, and place-scale relations. This article presents a review (2002–2018) of social innovation in urban spaces. Based on data from 114 publications, the review indicates that research in the spatiality of social innovation can be grouped into three major themes: (1) Spatial planning and community development; (2) Governance; (3) Co-production and service design. The findings suggest that in general the collaboration of end users in place-based development is central to this process of urban change and that process is as significant as the outcome. This article concludes with a research agenda to address identified lacunas

Reply to “Programming may matter most.” Response to “Metabolic effects of two high-intensity circuit training protocols: Does sequence matter?”

We appreciate the interest that our study elicited and the comments from a reader. We commend the reader of our paper for critically evaluating the protocol and results of the study. Here, we would like to respond to the statement made in the letter. Indeed, the rest intervals were longer and time at VO2max was lower in our study than recommended by Bucheit and Larsen.1 However, because the reader is interested in the practical implications of our study, we ask that they consider the following

Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments

[Multiple authors] In this paper, we propose a general architecture that is based on fast/slow solvers and a metacognitive component. We then present experimental results on the behavior of an instance of this architecture, for AI systems that make decisions about navigating in a constrained environment. We show how combining the fast and slow decision modalities allows the system to evolve over time and gradually pass from slow to fast thinking with enough experience, and that this greatly helps in decision quality, resource consumption, and efficiency

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Level 3: Sophie et sa grand-mère mystérieuse/ Sophie and her mysterious grandmother

This book is dedicated to all young students who want to learn. There is always more to learn and a way to learn it. Never stop dreaming. About the Author: My name is Nicholas Fabiano. I\u27m American. I am a student at the University of Kennesaw State in the United States. I\u27m studying electronic engineering. I like traveling, horse riding, boxing and spending time with my friends and family. Ce livre est dédié à tous les jeunes étudiants qui veulent apprendre. Il y a toujours plus à apprendre et un moyen de l\u27apprendre. N\u27arrêtez jamais de rêver. Je m’appelle Nicholas Fabiano. Je suis américain. Je suis étudiant à l’Université de Kennesaw State aux États-Unis. J’étudie l’ingénierie électronique. J\u27aime voyager, faire du cheval, boxer et passer du temps avec mes amis et ma famille.https://digitalcommons.kennesaw.edu/globallib/1003/thumbnail.jp

Emerging Places of Social Innovation (POSI). The co-production of space between multilevel stakeholders: the case of productive urban green infrastructure

Social innovation is recurrently positioned as an important collaborative element in helping cities to transition and address human needs and societal challenges for the health, wellbeing and welfare of citizens. To address a call for more sector-specific research on the spatiality of social innovation and further understanding of the process dimension of social innovation, this article presents a conceptual framework of the process of socio-spatial innovation. By combining social innovation insight from process theories and urban spaces discourse the article indicates that sociospatial innovation in the co-production of space can be grouped into four major processes: 1) Identification of human need or societal challenges to sustainable development; 2) Development of social relations in systems or structures; 3) Provision of opportunity for social empowerment; 4) Reflection of socio-spatial development practice. Applying this framework, the article examines how the case of productive green infrastructure emerges in the urban landscape as a Place of Social Innovation (POSI). The framework draws attention to the significance of partnership working and intermediation activities to improve access to urban spaces to contribute to socio-spatial justice and healthy orientated urban environments