Slow Cities: Sustainable Places in a Fast World

This article examines the Slow Food and Slow City movement as an alternative approach to urban development that focuses on local resources, economic and cultural strengths, and the unique historical context of a town. Following recent discussions about the politics of alternative economic development, the study examines the Slow City movement as a strategy to address the interdependencies between goals for economic, environmental, and equitable urban development. In particular, we draw on the examples of two Slow Cities in Germany—Waldkirch and Hersbruck, and show how these towns are retooling their urban policies. The study is placed in the context of alternative urban development agendas as opposed to corporate-centered development. We conclude the article by offering some remarks about the institutional and political attributes of successful Slow Cities and the transferability of the concept.

Fast Update of Conditional Simulation Ensembles

Gaussian random field (GRF) conditional simulation is a key ingredient in many spatial statistics problems for computing Monte-Carlo estimators and quantifying uncertainties on non-linear functionals of GRFs conditional on data. Conditional simulations are known to often be computer intensive, especially when appealing to matrix decomposition approaches with a large number of simulation points. This work studies settings where conditioning observations are assimilated batch sequentially, with one point or a batch of points at each stage. Assuming that conditional simulations have been performed at a previous stage, the goal is to take advantage of already available sample paths and by-products to produce updated conditional simulations at mini- mal cost. Explicit formulae are provided, which allow updating an ensemble of sample paths conditioned on n ≥ 0 observations to an ensemble conditioned on n + q observations, for arbitrary q ≥ 1. Compared to direct approaches, the proposed formulae proveto substantially reduce computational complexity. Moreover, these formulae explicitly exhibit how the q new observations are updating the old sample paths. Detailed complexity calculations highlighting the benefits of this approach with respect to state-of-the-art algorithms are provided and are complemented by numerical experiments.

Fast-twitch skeletal muscle fiber adaptation to SERCA1 deficiency in a Dutch Improved Red and White calf pseudomyotonia case.

Missense mutations in ATP2A1 gene, encoding SERCA1 protein, cause a muscle disorder designed as congenital pseudomyotonia (PMT) in Chianina and Romagnola cattle or congenital muscular dystonia1 (CMD1) in Belgian Blue cattle. Although PMT is not life-threatening, CMD1 affected calves usually die within a few weeks of age as a result of respiratory complication. We have recently described a muscular disorder in a double muscle Dutch Improved Red and White cross-breed calf. Mutation analysis revealed an ATP2A1 mutation identical to that described in CMD1, even though clinical phenotype was quite similar to that of PMT. Here, we provide evidence for a deficiency of mutated SERCA1 in PMT affected muscles of Dutch Improved Red and White calf, but not of its mRNA. The reduced expression of SERCA1 is selective and not compensated by the SERCA2 isoform. By contrast, pathological muscles are characterized by a broad distribution of mitochondrial markers in all fiber types, not related to intrinsic features of double muscle phenotype and by an increased expression of sarcolemmal calcium extrusion pump. Calcium removal mechanisms, operating in muscle fibers as compensatory response aimed at lowering excessive cytoplasmic calcium concentration caused by SERCA1 deficiency, could explain the difference in severity of clinical signs.

Development of a method for fast and automatic radiocarbon measurement of aerosol samples by online coupling of an elemental analyzer with a MICADAS AMS

A fast and automatic method for radiocarbon analysis of aerosol samples is presented. This type of analysis requires high number of sample measurements of low carbon masses, but accepts precisions lower than for carbon dating analysis. The method is based on online Trapping CO2 and coupling an elemental analyzer with a MICADAS AMS by means of a gas interface. It gives similar results to a previously validated reference method for the same set of samples. This method is fast and automatic and typically provides uncertainties of 1.5–5% for representative aerosol samples. It proves to be robust and reliable and allows for overnight and unattended measurements. A constant and cross contamination correction is included, which indicates a constant contamination of 1.4 ± 0.2 μg C with 70 ± 7 pMC and a cross contamination of (0.2 ± 0.1)% from the previous sample. A Real-time online coupling version of the method was also investigated. It shows promising results for standard materials with slightly higher uncertainties than the Trapping online approach.

Tracking the origins of Yakutian horses and the genetic basis for their fast adaptation to subarctic environments

Yakutia, Sakha Republic, in the Siberian Far East, represents one of the coldest places on Earth, with winter record temperatures dropping below -70 °C. Nevertheless, Yakutian horses survive all year round in the open air due to striking phenotypic adaptations, including compact body conformations, extremely hairy winter coats, and acute seasonal differences in metabolic activities. The evolutionary origins of Yakutian horses and the genetic basis of their adaptations remain, however, contentious. Here, we present the complete genomes of nine present-day Yakutian horses and two ancient specimens dating from the early 19th century and ∼5,200 y ago. By comparing these genomes with the genomes of two Late Pleistocene, 27 domesticated, and three wild Przewalski's horses, we find that contemporary Yakutian horses do not descend from the native horses that populated the region until the mid-Holocene, but were most likely introduced following the migration of the Yakut people a few centuries ago. Thus, they represent one of the fastest cases of adaptation to the extreme temperatures of the Arctic. We find cis-regulatory mutations to have contributed more than nonsynonymous changes to their adaptation, likely due to the comparatively limited standing variation within gene bodies at the time the population was founded. Genes involved in hair development, body size, and metabolic and hormone signaling pathways represent an essential part of the Yakutian horse adaptive genetic toolkit. Finally, we find evidence for convergent evolution with native human populations and woolly mammoths, suggesting that only a few evolutionary strategies are compatible with survival in extremely cold environments.

Fast Prediction of Femoral Biomechanics Using Supervised Machine Learning and Statistical Shape Modeling

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.

A fast protocol for purification of translating mRNAs

We present a protocol that enables easy extraction of translating mRNAs by purification of tagged ribosomes and associated mRNAs. By studying three different examples of stress influenced genes, we demonstrate the effectiveness and compare our rapid method to an older protocol (Halbeisen et al., 2009).

Temporally Coherent Disparity Maps Using CRFs with Fast 4D Filtering

State of the art methods for disparity estimation achieve good results for single stereo frames, but temporal coherence in stereo videos is often neglected. In this paper we present a method to compute temporally coherent disparity maps. We define an energy over whole stereo sequences and optimize their Conditional Random Field (CRF) distributions using mean-field approximation. We introduce novel terms for smoothness and consistency between the left and right views, and perform CRF optimization by fast, iterative spatio-temporal filtering with linear complexity in the total number of pixels. Our results rank among the state of the art while having significantly less flickering artifacts in stereo sequences.