Lit up and left dark: Failures of imagination in urban broadband networks

The design and deployment of urban broadband infrastructures inscribe particular imaginations of Internet access onto city streets. The different manifestations and locations of these networks, their uses, and access points often expose material excesses of urban broadband networks, as well as failures of Internet service providers, urban planners, and public officials to imagine the diverse ways that people incorporate Internet connection into their everyday lives. We approach the study of urban broadband networks through the juxtaposition of invisible networks that are buried under the streets and have always been “turned off” (dark fiber) versus hypervisible that are “turned on” and prominently displayed on city streets (LinkNYC). In our analysis of these two case studies, we critique themes of visibility and invisibility as indexes of power and access. Our findings are meant to provide a critical analysis of urban technology policy as well as theories of infrastructure, visibility, and access

Estimating confidence intervals in predicted responses for oscillatory biological models

BACKGROUND: The dynamics of gene regulation play a crucial role in a cellular control: allowing the cell to express the right proteins to meet changing needs. Some needs, such as correctly anticipating the day-night cycle, require complicated oscillatory features. In the analysis of gene regulatory networks, mathematical models are frequently used to understand how a network’s structure enables it to respond appropriately to external inputs. These models typically consist of a set of ordinary differential equations, describing a network of biochemical reactions, and unknown kinetic parameters, chosen such that the model best captures experimental data. However, since a model’s parameter values are uncertain, and since dynamic responses to inputs are highly parameter-dependent, it is difficult to assess the confidence associated with these in silico predictions. In particular, models with complex dynamics - such as oscillations - must be fit with computationally expensive global optimization routines, and cannot take advantage of existing measures of identifiability. Despite their difficulty to model mathematically, limit cycle oscillations play a key role in many biological processes, including cell cycling, metabolism, neuron firing, and circadian rhythms. RESULTS: In this study, we employ an efficient parameter estimation technique to enable a bootstrap uncertainty analysis for limit cycle models. Since the primary role of systems biology models is the insight they provide on responses to rate perturbations, we extend our uncertainty analysis to include first order sensitivity coefficients. Using a literature model of circadian rhythms, we show how predictive precision is degraded with decreasing sample points and increasing relative error. Additionally, we show how this method can be used for model discrimination by comparing the output identifiability of two candidate model structures to published literature data. CONCLUSIONS: Our method permits modellers of oscillatory systems to confidently show that a model’s dynamic characteristics follow directly from experimental data and model structure, relaxing assumptions on the particular parameters chosen. Ultimately, this work highlights the importance of continued collection of high-resolution data on gene and protein activity levels, as they allow the development of predictive mathematical models

EFFETS PRÉCOCES D'UNE BRÈVE ÉLÉVATION DE LA TEMPÉRATURE TESTICULAIRE SUR LA SPERMATOGENÈSE DU BÉLIER

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