scholarly journals ECOLOGIA DO MOVIMENTO EM PEIXES DE RIACHO

2021 ◽  
Vol 25 (02) ◽  
pp. 381-397
Author(s):  
Rosana Mazzoni ◽  
◽  
Thiago Fonseca de Barros ◽  
Keyword(s):  
Large Scale ◽  
Temporal Structure ◽  
Spatial Dynamics ◽  
Fish Movement ◽  
Neotropical Fish ◽  
Neotropical Streams ◽  
Key Factor ◽  
Spatio Temporal ◽  
And Performance ◽  
Analytical Tools

Movement is a key factor in spatial dynamics and the size of fish populations. It is one of the main mechanisms for maintaining viable populations and also accounts for the dispersion, colonization and performance of individuals life stages. The currently refuted restricted movement paradigm predicted that freshwater fish would not move. However, studies show that in addition to moving on a short and large scale, the movement patterns of these fish have, in general, reproductive, food, search for shelter, colonization or exploitation motivation. Studies on the movement of Neotropical fish are concentrated on the large migrators from large basins, such as Amazonas and Paraná. For streams, where small species predominate, little is known about the movement and its motivations. In this review, we show that studies on the movement of fish in neotropical streams are still very scarce. We propose a protocol for obtaining data and analytical tools for determining fish movement in streams. We highlight three tools for that: (i) analysis of the spatio-temporal structure of the size of the fish, (ii) mark-recapture experiments and (iii) molecular analyzes. We conclude that, given the limitation of each analysis, the use of the three tools must be carried out jointly.

scholarly journals Meditation-induced effects on whole-brain structural and effective connectivity

2021 ◽  
Author(s):  
Eleonora De Filippi ◽  
Anira Escrichs ◽  
Matthieu Gilson ◽  
Marti Sanchez-Fibla ◽  
Estela Camara ◽  
...  
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Effective Connectivity ◽  
Temporal Structure ◽  
Functional Domain ◽  
Anatomical Connectivity ◽  
Whole Brain ◽  
Spatio Temporal ◽  
Large Scale Networks ◽  
And Function

In the past decades, there has been a growing scientific interest in characterizing neural correlates of meditation training. Nonetheless, the mechanisms underlying meditation remain elusive. In the present work, we investigated meditation-related changes in structural and functional connectivities (SC and FC, respectively). For this purpose, we scanned experienced meditators and control (naive) subjects using magnetic resonance imaging (MRI) to acquire structural and functional data during two conditions, resting-state and meditation (focused attention on breathing). In this way, we aimed to characterize and distinguish both short-term and long-term modifications in the brain's structure and function. First, we performed a network-based analysis of anatomical connectivity. Then, to analyze the fMRI data, we calculated whole-brain effective connectivity (EC) estimates, relying on a dynamical network model to replicate BOLD signals' spatio-temporal structure, akin to FC with lagged correlations. We compared the estimated EC, FC, and SC links as features to train classifiers to predict behavioral conditions and group identity. The whole-brain SC analysis revealed strengthened anatomical connectivity across large-scale networks for meditators compared to controls. We found that differences in SC were reflected in the functional domain as well. We demonstrated through a machine-learning approach that EC features were more informative than FC and SC solely. Using EC features we reached high performance for the condition-based classification within each group and moderately high accuracies when comparing the two groups in each condition. Moreover, we showed that the most informative EC links that discriminated between meditators and controls involved the same large-scale networks previously found to have increased anatomical connectivity. Overall, the results of our whole-brain model-based approach revealed a mechanism underlying meditation by providing causal relationships at the structure-function level.

scholarly journals Meditation-Induced Effects on Whole-Brain Structural and Effective Connectivity

2021 ◽  
Author(s):  
Eleonora De Filippi ◽  
Anira Escrichs ◽  
Estela Càmara ◽  
César Garrido ◽  
Martí Sánchez-Fibla ◽  
...  
Keyword(s):  
Large Scale ◽  
Effective Connectivity ◽  
Temporal Structure ◽  
Functional Domain ◽  
Anatomical Connectivity ◽  
Whole Brain ◽  
Spatio Temporal ◽  
Magnetic Resonance Imaging Mri ◽  
Large Scale Networks ◽  
And Function

Abstract In the past decades, there has been a growing scientific interest in characterizing neural correlates of meditation training. Nonetheless, the mechanisms underlying meditation remain elusive. In the present work, we investigated meditation-related changes in structural and functional connectivities (SC and FC, respectively). For this purpose, we scanned experienced meditators and control (naive) subjects using magnetic resonance imaging (MRI) to acquire structural and functional data during two conditions, resting-state and meditation (focused attention on breathing). In this way, we aimed to characterize and distinguish both short-term and long-term modifications in the brain's structure and function. First, we performed a network-based analysis of anatomical connectivity. Then, to analyze the fMRI data, we calculated whole-brain effective connectivity (EC) estimates, relying on a dynamical network model to replicate BOLD signals' spatio-temporal structure, akin to FC with lagged correlations. We compared the estimated EC, FC, and SC links as features to train classifiers to predict behavioral conditions and group identity. The whole-brain SC analysis revealed strengthened anatomical connectivity across large-scale networks for meditators compared to controls. We found that differences in SC were reflected in the functional domain as well. We demonstrated through a machine-learning approach that EC features were more informative than FC and SC solely. Moreover, we showed that the most informative EC links that discriminated between meditators and controls involved the same large-scale networks previously found to have increased anatomical connectivity. Overall, the results of our whole-brain model-based approach revealed a mechanism underlying meditation by providing causal relationships at the structure-function level.

scholarly journals Inferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maria Choufany ◽  
Davide Martinetti ◽  
Samuel Soubeyrand ◽  
Cindy E. Morris
Keyword(s):  
Large Scale ◽  
Mass Movement ◽  
Geographical Area ◽  
Small World ◽  
Long Distance ◽  
Air Mass ◽  
Key Factor ◽  
Large Geographical Area ◽  
Spatio Temporal ◽  
Small World Property

AbstractThe collection and analysis of air samples for the study of microbial airborne communities or the detection of airborne pathogens is one of the few insights that we can grasp of a continuously moving flux of microorganisms from their sources to their sinks through the atmosphere. For large-scale studies, a comprehensive sampling of the atmosphere is beyond the scopes of any reasonable experimental setting, making the choice of the sampling locations and dates a key factor for the representativeness of the collected data. In this work we present a new method for revealing the main patterns of air-mass connectivity over a large geographical area using the formalism of spatio-temporal networks, that are particularly suitable for representing complex patterns of connection. We use the coastline of the Mediterranean basin as an example. We reveal a temporal pattern of connectivity over the study area with regions that act as strong sources or strong receptors according to the season of the year. The comparison of the two seasonal networks has also allowed us to propose a new methodology for comparing spatial weighted networks that is inspired from the small-world property of non-spatial networks.

Composing And Performing Complex Systems: From The Quantum To The Cosmological

Leonardo ◽  
2021 ◽  
pp. 1-7
Author(s):  
JoAnn Kuchera-Morin
Keyword(s):  
Large Scale ◽  
Orchestral Music ◽  
Data Sets ◽  
Complex Data ◽  
Instrumental Ensemble ◽  
Complex Data Sets ◽  
Temporal Structures ◽  
Multi Media ◽  
Spatio Temporal ◽  
And Performance

Abstract This paper discusses the creation and development of a large distributed immersive multimedia computation system and environment based on the discipline of orchestral music composition, concert hall design, and performance. Just as the orchestra evolved through mechanical engineering to become a large distributed multi-user instrument whose information can be transmitted either by a client-server model as in orchestra-conductor, or a client-to-client model, as in an instrumental ensemble, large-scale distributed multi-media computational platforms can be modeled in the same way, facilitating the users as performers of the system. Multiple researchers can mine large, complex data sets to uncover important relationships in their spatio-temporal structures.

Communication Analysis and Performance Prediction of Parallel Applications on Large-Scale Machines

2016 ◽  
pp. 80-105 ◽  
Author(s):  
Yan Li ◽  
Jidong Zhai ◽  
Keqin Li
Keyword(s):  
Performance Prediction ◽  
High Performance ◽  
Large Scale ◽  
Computation Time ◽  
Parallel Applications ◽  
Network Simulator ◽  
Communication Performance ◽  
Key Factor ◽  
And Performance ◽  
High Performance Computers

With the development of high performance computers, communication performance is a key factor affecting the performance of HPC applications. Communication patterns can be obtained by analyzing communication traces. However, existing approaches to generating communication traces need to execute the entire parallel applications on full-scale systems that are time-consuming and expensive. Furthermore, for designers of large-scale parallel computers, it is greatly desired that performance of a parallel application can be predicted at the design phase. Despite previous efforts, it remains an open problem to estimate sequential computation time in each process accurately and efficiently for large-scale parallel applications on non-existing target machines. In this chapter, we will introduce a novel technique for performing fast communication trace collection for large-scale parallel applications and an automatic performance prediction framework with a trace-driven network simulator.

scholarly journals Applied translation studies and transdisciplinary action research: Understanding, learning and transforming translation in professional contexts

2021 ◽  
Vol 25 (2) ◽  
pp. 443-461
Author(s):  
Gary Massey
Keyword(s):  
Action Research ◽  
Large Scale ◽  
Translation Studies ◽  
Use Case ◽  
The Past ◽  
Home Institution ◽  
Key Factor ◽  
And Performance ◽  
Professional Contexts

Proceeding from accepted shared definitions of applied linguistics that stress its practical, real-world orientation and instrumentality, this article seeks to move the focus from the interdisciplinarity that has been identified as the nexus of translation studies in the past to how its applied branches should systematically engage with an emerging transdisciplinary research paradigm. It argues that the shift can and will be a key factor, challenge and opportunity in the onward development of applied translation studies as it seeks to adequately address the situated realities of professional translation. The article reveals how transdisciplinarity, operationalised as action research, offers a viable framework for investigating, understanding and learning about what translators really do in working contexts and settings, with a view to identifying issues, improving practices, processes and performance, and ultimately transforming the profession for the good of those it employs and serves. In doing so, it considers approaches from cognitive translatology, based largely on a 4EA cognitive paradigm, and translatorial linguistic ethnography, where researchers are gradually but progressively going out into the field to explore and describe the complex socio-cognitive, socio-technical activity of translation in situ. After presenting a use case from a large-scale research project on translation ergonomics at the authors home institution, the article puts forward a model for transdisciplinary action research in professional settings to guide the necessary transition from interdisciplinarity to transdisciplinarity. Such a model would allow professional processes and practices to be investigated, and the findings productively and transformatively applied, in the situated socio-cognitive and socio-technical contexts of translators workplaces - within, for, with and by the organisations that employ them.

Sensing Ionospheric Turbulence Using GNSS

2020 ◽  
Author(s):  
Giulio Tagliaferro ◽  
Andrea Gatti ◽  
Eugenio Realini
Keyword(s):  
Structure Function ◽  
Power Law ◽  
Large Scale ◽  
Ionospheric Plasma ◽  
Temporal Structure ◽  
Turbulent Medium ◽  
Structure Characteristic ◽  
Small Scale ◽  
Polar Regions ◽  
Spatio Temporal

<p>Electron density in ionospheric plasma exhibits fluctuations and irregularities in time and space, at several scales. Plasma, being ionized gas, is subject to a turbulent behaviour similar to that observed in fluid dynamics, with two main distinctions: a) its dynamics are coupled with electromagnetic fields; b) collisions of particles are rare. These unique properties characterize the inertial range of ionospheric plasma turbulence, which represents the energy cascade from large-scale structures (e.g. travelling ionospheric disturbances) to small-scale ones (eddies) until energy dissipation occurs. </p><p>Kolmogorov power law would predict a spectrum of 8/3 and equivalently a structure function with a power law of 5/3 for a phase signal crossing a 3D turbulent medium. However, the previous investigation of spatial structure characteristic of the ionosphere using LOFAR array observed a power law of around 1.9 in the spatial domain. In this study, we investigate the spatio-temporal and temporal structure of the ionosphere using structure function of GNSS phase geometry free signals from both medium earth orbit satellites and geostationary ones. We found two regimes, one compatible the 5/3 Kolmogorov theory and one obeying a 2 power law. We propose an interpretation for the two regimes, the first being a 3D turbulent flow driven by local instabilities, and the second one being driven by solar radiation-induced ionization and successive recombination. The second spectrum obeys a power law of 2, that is the power spectrum of a sinusoidal function like the local sun elevation. By using receivers at almost constant solar irradiance located in polar regions, we further observe the turbulent regimes also in spatio-temporal structure function.</p>

scholarly journals Spatio-temporal spectra in the logarithmic layer of wall turbulence: large-eddy simulations and simple models

2015 ◽  
Vol 769 ◽  
Author(s):  
Michael Wilczek ◽  
Richard J. A. M. Stevens ◽  
Charles Meneveau
Keyword(s):  
Large Scale ◽  
Temporal Structure ◽  
Streamwise Velocity ◽  
Wall Turbulence ◽  
Mean Flow ◽  
Frequency Spectra ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Spatio Temporal ◽  
Logarithmic Layer

Motivated by the need to characterize the spatio-temporal structure of turbulence in wall-bounded flows, we study wavenumber–frequency spectra of the streamwise velocity component based on large-eddy simulation (LES) data. The LES data are used to measure spectra as a function of the two wall-parallel wavenumbers and the frequency in the equilibrium (logarithmic) layer. We then reformulate one of the simplest models that is able to reproduce the observations: the random sweeping model with a Gaussian large-scale fluctuating velocity and with additional mean flow. Comparison with LES data shows that the model captures the observed temporal decorrelation, which is related to the Doppler broadening of frequencies. We furthermore introduce a parameterization for the entire wavenumber–frequency spectrum $E_{11}(k_{1},k_{2},{\it\omega};z)$, where $k_{1}$, $k_{2}$ are the streamwise and spanwise wavenumbers, ${\it\omega}$ is the frequency and $z$ is the distance to the wall. The results are found to be in good agreement with LES data.

Going the Distance

2020 ◽  
Author(s):  
Ron Harris
Keyword(s):  
Large Scale ◽  
Western Europe ◽  
Family Firms ◽  
Global Trade ◽  
Long Distance ◽  
Business Corporation ◽  
Modern Economy ◽  
Key Factor ◽  
Silk Route ◽  
Passive Investors

Before the seventeenth century, trade across Eurasia was mostly conducted in short segments along the Silk Route and Indian Ocean. Business was organized in family firms, merchant networks, and state-owned enterprises, and dominated by Chinese, Indian, and Arabic traders. However, around 1600 the first two joint-stock corporations, the English and Dutch East India Companies, were established. This book tells the story of overland and maritime trade without Europeans, of European Cape Route trade without corporations, and of how new, large-scale, and impersonal organizations arose in Europe to control long-distance trade for more than three centuries. It shows that by 1700, the scene and methods for global trade had dramatically changed: Dutch and English merchants shepherded goods directly from China and India to northwestern Europe. To understand this transformation, the book compares the organizational forms used in four major regions: China, India, the Middle East, and Western Europe. The English and Dutch were the last to leap into Eurasian trade, and they innovated in order to compete. They raised capital from passive investors through impersonal stock markets and their joint-stock corporations deployed more capital, ships, and agents to deliver goods from their origins to consumers. The book explores the history behind a cornerstone of the modern economy, and how this organizational revolution contributed to the formation of global trade and the creation of the business corporation as a key factor in Europe's economic rise.

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