https://hdl.handle.net/2072/478914 Wed, 08 Apr 2026 10:37:27 GMT 2026-04-08T10:37:27Z https://hdl.handle.net/2445/224948 Trends and drivers of pedestrian mobility in Barcelona: A fine-grained study across its commercial tissue Rames, Clément; Rhoads, Daniel; Meseguer Artola, Antoni; Lozano, Sergi; Borge Holthoefer, Javier; Solé Ribalta, Albert Identifying factors that promote active mobility, especially walking, is essential for designing resilient and livable cities and promoting sustainable urban mobility. In spite of recent advances in this direction, available data often remains too spatially and temporally coarse, which constrains analysis. This paper leverages high resolution data from over 200 pedestrian count sensors, placed along Barcelona’s commercial areas, providing a detailed understanding of how walking volume has evolved over the past five years, how it varies across neighborhoods, and which socioeconomic and urban attributes influence it. We find that while overall pedestrian traffic has increased, a neighborhood-scale analysis reveals a nuanced picture of fluctuations, including increases, declines, and periodic patterns. The use of global regression models allows us to identify seven key urban factors that shape pedestrian mobility. Subsequently moving the analysis to spatially-aware regression models, we identify the spatial non-stationarity of these factors across the city, indicating the presence of distinct behavioral groups within the urban population. The detailed spatial resolution of our findings provides municipal decision-makers with insights for implementing precise interventions and continually evaluating their effects. Moreover, monitoring pedestrian traffic before and after urban initiatives, while adjusting for seasonal, daily, and time-of-day variations, can yield critical insights for developing pedestrian-oriented urban environments. Mon, 15 Dec 2025 17:50:20 GMT https://hdl.handle.net/2445/224948 2025-12-15T17:50:20Z https://hdl.handle.net/2445/222200 Discounting the Distant Future: What Do Historical Bond Prices Imply about the Long-Term Discount Rate? Farmer, J. Doyne; Geanakoplos, John; Richiardi, Matteo G.; Montero Matellanes, M. Mikel; Perelló, Josep, 1974-; Masoliver, Jaume, 1951- We present a thorough empirical study on real interest rates by also including risk aversion through the introduction of the market price of risk. From the viewpoint of complex systems science and its multidisciplinary approach, we use the theory of bond pricing to study the long-term discount rate to estimate the rate when taking historical US and UK data, and to further contribute to the discussion about the urgency of climate action in the context of environmental economics and stochastic methods. Century-long historical records of 3-month bonds, 10-year bonds, and inflation allow us to estimate real interest rates for the UK and the US. Real interest rates are negative about a third of the time and the real yield curves are inverted more than a third of the time, sometimes by substantial amounts. This rules out most of the standard bond-pricing models, which are designed for nominal rates that are assumed to be positive. We, therefore, use the Ornstein–Uhlenbeck model, which allows negative rates and gives a good match to inversions of the yield curve. We derive the discount function using the method of Fourier transforms and fit it to the historical data. The estimated long-term discount rate is 1.7% for the UK and 2.2% for the US. The value of 1.4% used by Stern is less than a standard deviation from our estimated long-run return rate for the UK, and less than two standard deviations of the estimated value for the US. All of this once more reinforces the need for immediate and substantial spending to combat climate change. Mon, 14 Jul 2025 10:17:26 GMT https://hdl.handle.net/2445/222200 2025-07-14T10:17:26Z https://hdl.handle.net/2445/200656 Astrocyte dysfunction and neuronal network hyperactivity in a CRISPR engineered pluripotent stem cell model of frontotemporal dementia Canals, Isaac; Comella Bolla, Andrea; Cepeda-Prado, Efrain; Avaliani, Natalia; Crowe, James A.; Oburoglu, Leal; Bruzelius, Andreas; King, Naomi; Pajares, María A.; Pérez-Sala, Dolores; Heuer, Andreas; Rylander Ottosson, Daniella; Soriano i Fradera, Jordi; Ahlenius, Henrik Frontotemporal dementia (FTD) is the second most prevalent type of early-onset dementia and up to 40% of cases are familial forms. One of the genes mutated in patients is CHMP2B, which encodes a protein found in a complex important for maturation of late endosomes, an essential process for recycling membrane proteins through the endolysosomal system. Here, we have generated a CHMP2B-mutated human embryonic stem cell line using genome editing with the purpose to create a human in vitro FTD disease model. To date, most studies have focused on neuronal alterations; however, we present a new co-culture system in which neurons and astrocytes are independently generated from human embryonic stem cells and combined in co-cultures. With this approach, we have identified alterations in the endolysosomal system of FTD astrocytes, a higher capacity of astrocytes to uptake and respond to glutamate, and a neuronal network hyperactivity as well as excessive synchronization. Overall, our data indicates that astrocyte alterations precede neuronal impairments and could potentially trigger neuronal network changes, indicating the important and specific role of astrocytes in disease development. Fri, 14 Jul 2023 14:39:58 GMT https://hdl.handle.net/2445/200656 2023-07-14T14:39:58Z https://hdl.handle.net/2445/122334 Dominance of metric correlations in two-dimensional neuronal cultures described through a Random Field Ising Model Hernández Navarro, Lluís; Gómez Orlandi, Javier; Cerruti, Benedetta; Vives i Santa-Eulàlia, Eduard; Soriano i Fradera, Jordi We introduce a novel random field Ising model, grounded on experimental observations, to assess the importance of metric correlations in cortical circuits in vitro. Metric correlations arise from both the finite axonal length and the heterogeneity in the spatial arrangement of neurons. The experiments consider the response of neuronal cultures to an external electric stimulation for a gradually weaker connectivity strength between neurons, and in cultures with different spatial configurations. The model can be analytically solved in the metric-free, mean-field scenario. The presence of metric correlations precipitates a strong deviation from the mean field. Null models of the same networks that preserve the distribution of connections recover the mean field. Our results show that metric-inherited correlations in spatial networks dominate the connectivity blueprint, mask the actual distribution of connections, and may emerge as the asset that shapes network dynamics. Mon, 14 May 2018 15:08:22 GMT https://hdl.handle.net/2445/122334 2018-05-14T15:08:22Z