Search results for "Quantitative"

The community structure of the global corporate network.

2013

We investigate the community structure of the global ownership network of transnational corporations. We find a pronounced organization in communities that cannot be explained by randomness. Despite the global character of this network, communities reflect first of all the geographical location of firms, while the industrial sector plays only a marginal role. We also analyze the network in which the nodes are the communities and the links are obtained by aggregating the links among firms belonging to pairs of communities. We analyze the network centrality of the top 50 communities and we provide the first quantitative assessment of the financial sector role in connecting the global economy.

Topology of synaptic connectivity constrains neuronal stimulus representation, predicting two complementary coding strategies

2022

In motor-related brain regions, movement intention has been successfully decoded from in-vivo spike train by isolating a lower-dimension manifold that the high-dimensional spiking activity is constrained to. The mechanism enforcing this constraint remains unclear, although it has been hypothesized to be implemented by the connectivity of the sampled neurons. We test this idea and explore the interactions between local synaptic connectivity and its ability to encode information in a lower dimensional manifold through simulations of a detailed microcircuit model with realistic sources of noise. We confirm that even in isolation such a model can encode the identity of different stimuli in a lo…

Quantitative assessment of the parameters linked to the blending between reclaimed asphalt binder and recycling agent: A literature review

2020

Abstract The lack of understanding the mechanisms governing the interaction between reclaimed asphalt binder (RAb) 1 and recycling agents is one of the technical issues that still need to be resolved when high amount of reclaimed asphalt (RA) 2 is used in a new recycled asphalt mixture (RAM). Due to important role of RAb in that interaction and increased used of RA, it becomes necessary to have a way to classify RA, as any other material used in asphalt mixture production. It is very important to determine how much RAb is active by itself (DoA) 3 , but also to determine how much RAb can be considered available for a mix design of RAM (DoAv) 4 when a recycling agent is used. Finally, since t…

Enriqueciendo la investigación en humanidades digitales. Análisis de textos de claustros académicos de la Universidad de Valencia (1775-1779) con KH …

2020

[ES] La aplicación de métodos automatizados en cualquier investigación ha facilitado el trasvase de metodologías de una disciplina a otra, permitiendo realizar análisis cuantitativos a textos con estructura o semiestructurados. El objeto de este trabajo es aplicar a un dataset en lenguaje natural -castellano del siglo XVIII- métodos de análisis de la disciplina de documentación. Pretende establecer una metodología automática de análisis cuantitativo y cualitativo de textos, que permita enriquecer en el futuro las conclusiones procedentes del análisis histórico tradicional. Este estudio construye los procedimientos necesarios para poder aplicar análisis de frecuencia, extracción y clasificac…

2020

Abstract Efficient neuronal communication between brain regions through oscillatory synchronization at certain frequencies is necessary for cognition. Such synchronized networks are transient and dynamic, established on the timescale of milliseconds in order to support ongoing cognitive operations. However, few studies characterizing dynamic electrophysiological brain networks have simultaneously accounted for temporal non-stationarity, spectral structure, and spatial properties. Here, we propose an analysis framework for characterizing the large-scale phase-coupling network dynamics during task performance using magnetoencephalography (MEG). We exploit the high spatiotemporal resolution of…

Non-equilibrium Markov state modeling of periodically driven biomolecules

2019

Molecular dynamics simulations allow to study the structure and dynamics of single biomolecules in microscopic detail. However, many processes occur on time scales beyond the reach of fully atomistic simulations and require coarse-grained multiscale models. While systematic approaches to construct such models have become available, these typically rely on microscopic dynamics that obey detailed balance. In vivo, however, biomolecules are constantly driven away from equilibrium in order to perform specific functions and thus break detailed balance. Here we introduce a method to construct Markov state models for systems that are driven through periodically changing one (or several) external p…

On Contextuality in Behavioral Data

2015

Dzhafarov, Zhang, and Kujala (Phil. Trans. Roy. Soc. A 374, 20150099) reviewed several behavioral data sets imitating the formal design of the quantum-mechanical contextuality experiments. The conclusion was that none of these data sets exhibited contextuality if understood in the generalized sense proposed in Dzhafarov, Kujala, and Larsson (Found. Phys. 7, 762-782, 2015), while the traditional definition of contextuality does not apply to these data because they violate the condition of consistent connectedness (also known as marginal selectivity, no-signaling condition, no-disturbance principle, etc.). In this paper we clarify the relationship between (in)consistent connectedness and (non…

Multiscale Granger causality analysis by à trous wavelet transform

2017

Since interactions in neural systems occur across multiple temporal scales, it is likely that information flow will exhibit a multiscale structure, thus requiring a multiscale generalization of classical temporal precedence causality analysis like Granger's approach. However, the computation of multiscale measures of information dynamics is complicated by theoretical and practical issues such as filtering and undersampling: to overcome these problems, we propose a wavelet-based approach for multiscale Granger causality (GC) analysis, which is characterized by the following properties: (i) only the candidate driver variable is wavelet transformed (ii) the decomposition is performed using the…

Improving light propagation Monte Carlo simulations with accurate 3D modeling of skin tissue

2008

In this paper, we present a 3D light propagation model to simulate multispectral reflectance images of large skin surface areas. In particular, we aim to simulate more accurately the effects of various physiological properties of the skin in the case of subcutaneous vein imaging compared to existing models. Our method combines a Monte Carlo light propagation model, a realistic three-dimensional model of the skin using parametric surfaces and a vision system for data acquisition. We describe our model in detail, present results from the Monte Carlo modeling and compare our results with those obtained with a well established Monte Carlo model and with real skin reflectance images.

Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics

2012

In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESC), exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing s…