PLANT: A Method for Detecting Changes of Slope in Noisy Trajectories

Time traces obtained from a variety of biophysical experiments contain valuable information on underlying processes occurring at the molecular level. Accurate quantification of these data can help explain the details of the complex dynamics of biological systems. Here, we describe PLANT (Piecewise Linear Approximation of Noisy Trajectories), a segmentation algorithm that allows the reconstruction of time-trace data with constant noise as consecutive straight lines, from which changes of slopes and their respective durations can be extracted. We present a general description of the algorithm and perform extensive simulations to characterize its strengths and limitations, providing a rationale for the performance of the algorithm in the different conditions tested. We further apply the algorithm to experimental data obtained from tracking the centroid position of lymphocytes migrating under the effect of a laminar flow and from single myosin molecules interacting with actin in a dual-trap force-clamp configuration.The authors gratefully acknowledge financial support fromthe European Commission (FP7-ICT-2011-7, grant number 288263), Erasmus Mundus Doctorate Program Europhoton-ics (grant number 159224-1-2009-1-FR-ERA MUNDUS-EMJD), Spanish Ministry of Economy and Competi-tiveness (“Severo Ochoa” Programme for Centres of Excellence in Research & Development SEV-2015-0522,and FIS2014-56107-R grants), Generalitat de Catalunyathrough the CERCA program, Italian Ministry of Uni-versity and Research (FIRB “Futuro in Ricerca” 2013grant n. RBFR13V4M2 and Flagship Project NANOMAX),Fundaci ́o Privada CELLEX (Barcelona), Ente Cassa diRisparmio di Firenze, Human Frontier Science Program (GARGP0027/2012) and LaserLab Europe 4 (GA 654148). C.M.acknowledges funding from the Spanish Ministry of Econ-omy and Competitiveness (MINECO) and the EuropeanSocial Fund (ESF) through the Ram ́on y Cajal program 2015(RYC-2015-17896).Peer ReviewedPostprint (author's final draft

Attractive streetscape making pedestrians walk longer routes: the case of Kunitachi in Tokyo

There are manifold benefits of an increase in pedestrian movement, both in regard to societal and to personal wellbeing, and walkability is considered a major goal in urban design. However, it is methodologically complicated to ascertain to what extent streetscape features relating to comfort and pleasurability influence pedestrian behavior. Our hypothesis is that pedestrians, at the neighborhood scale, prefer more attractive routes even if they are longer than other possible and equally safe routes to reach a certain destination, independently of the presence of amenities. As a case study, we selected Kunitachi, an attractive city in Tokyo Prefecture, thus adding to the body of non-western empirical research on pedestrian preferences. By comparing two Space Syntax betweenness simulations of pedestrian routes – compulsory and optional – with an actual counting of pedestrian frequency on site, and with behavioral observations, we have established that simulations according to the principle of “shortest route” considerably differ from actual pedestrian frequency. Only by allowing a certain detour leeway, simulations showed a less pronounced discrepancy with reality. While further research is needed to confirm our results, this enquiry has demonstrated that, attractive streetscape features are part of the reason why local residents prefer pleasant and comfortable routes over shorter ones

Science by the sea: how nanoengineering met mechanobiology in Camogli

No abstract available