Kuramoto dynamics, glassy synchronization and rare regions in the human connectome - Pablo Villegas
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The document discusses the Kuramoto model of synchronization and its application to modeling the human connectome. It finds that the connectome exhibits a hierarchical synchronization process, with local phase transitions leading to an intermediate synchronized phase. This behavior is also seen in hierarchical modular network models of the connectome. Both the real connectome data and model networks show switching or "up and down" states of metastability in the intermediate synchronization phase.
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The document discusses econophysics and the instability of the financial system caused by credit risk. It outlines the topics to be covered, including a structural model of credit risk, numerical simulations, and a random matrix approach. The conclusions discuss how risk reduction through diversification in credit portfolios is limited by correlations between credit exposures and the presence of jumps in the economic variables modeling the credit risks. Large portfolios do not necessarily converge to a Gaussian loss distribution due to these effects.Econophysics VI: Price Cross-Responses in Correlated Financial Markets - Thom...
Econophysics VI: Price Cross-Responses in Correlated Financial Markets - Thom...Lake Como School of Advanced Studies
1) The document analyzes price formation and cross-responses between correlated financial markets using empirical data from NASDAQ stocks. It finds long-memory correlations between the trades and prices of different stocks.
2) Specifically, it measures the cross-response of one stock's price changes to the trades of other stocks, and the cross-correlation between stocks' trade signs. It finds these cross-responses and cross-correlations decay slowly over time, indicating long-range correlations.
3) Averaging the cross-responses and cross-correlations across stocks reduces noise and more clearly reveals their long-memory nature. The analysis provides evidence that liquidity and trading in one stock can have prolonged impacts on price formationEconophysics V: Market States and Subtleties of Correlations - Thomas Guhr
Econophysics V: Market States and Subtleties of Correlations - Thomas GuhrLake Como School of Advanced Studies
This document discusses market states and correlations between financial time series. It begins by introducing the Epps effect, where measured correlations decrease with smaller time intervals, and describes compensating for this using asynchronity and tick size corrections. Non-Gaussian dependencies are then covered, showing correlations can misrepresent relationships. Market states are identified using similarity measures between correlation matrices over time. Eight distinct market states are found for the US market between 1992-2010 based on industrial sector correlations.More from Lake Como School of Advanced Studies (20)
Electromagnetic counterparts of Gravitational Waves - Elena Pian
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LOW FREQUENCY GW SOURCES: Chapter III: Probing massive black hole binary with...
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LOW FREQUENCY GW SOURCES: Chapter II: Massive black hole binary cosmic evolut...
LOW FREQUENCY GW SOURCES: Chapter I: Overview of LISA sources - Alberto Sesana
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Gravitational waves data analysis - Walter Del Pozzo
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Space based Gravitational Wave Observations I – M Hewitson from Lake Como Sch...
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Space based Gravitational Wave Observations II - M Hewitson
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Econophysics VII: Credits and the Instability of the Financial System - Thoma...
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Econophysics V: Market States and Subtleties of Correlations - Thomas Guhr
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Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
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Methods of grain storage Structures in India.pdf
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•Totalfoodgrainproductioninindiais311milliontonnesandstorageis145mt.InIndia,annualstoragelosseshavebeenestimated14mtworthofRs.7,000croreinwhichinsectsaloneaccountfornearlyRs.1,300crores.
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The debris of the ‘last major merger’ is dynamically young
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Context. The observation of several L-band emission sources in the S cluster has led to a rich discussion of their nature. However, a definitive answer to the classification of the dusty objects requires an explanation for the detection of compact Doppler-shifted Brγ emission. The ionized hydrogen in combination with the observation of mid-infrared L-band continuum emission suggests that most of these sources are embedded in a dusty envelope. These embedded sources are part of the S-cluster, and their relationship to the S-stars is still under debate. To date, the question of the origin of these two populations has been vague, although all explanations favor migration processes for the individual cluster members. Aims. This work revisits the S-cluster and its dusty members orbiting the supermassive black hole SgrA* on bound Keplerian orbits from a kinematic perspective. The aim is to explore the Keplerian parameters for patterns that might imply a nonrandom distribution of the sample. Additionally, various analytical aspects are considered to address the nature of the dusty sources. Methods. Based on the photometric analysis, we estimated the individual H−K and K−L colors for the source sample and compared the results to known cluster members. The classification revealed a noticeable contrast between the S-stars and the dusty sources. To fit the flux-density distribution, we utilized the radiative transfer code HYPERION and implemented a young stellar object Class I model. We obtained the position angle from the Keplerian fit results; additionally, we analyzed the distribution of the inclinations and the longitudes of the ascending node. Results. The colors of the dusty sources suggest a stellar nature consistent with the spectral energy distribution in the near and midinfrared domains. Furthermore, the evaporation timescales of dusty and gaseous clumps in the vicinity of SgrA* are much shorter ( 2yr) than the epochs covered by the observations (≈15yr). In addition to the strong evidence for the stellar classification of the D-sources, we also find a clear disk-like pattern following the arrangements of S-stars proposed in the literature. Furthermore, we find a global intrinsic inclination for all dusty sources of 60 ± 20◦, implying a common formation process. Conclusions. The pattern of the dusty sources manifested in the distribution of the position angles, inclinations, and longitudes of the ascending node strongly suggests two different scenarios: the main-sequence stars and the dusty stellar S-cluster sources share a common formation history or migrated with a similar formation channel in the vicinity of SgrA*. Alternatively, the gravitational influence of SgrA* in combination with a massive perturber, such as a putative intermediate mass black hole in the IRS 13 cluster, forces the dusty objects and S-stars to follow a particular orbital arrangement. Key words. stars: black holes– stars: formation– Galaxy: center– galaxies: star formation
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...Advanced-Concepts-Team
Presentation in the Science Coffee of the Advanced Concepts Team of the European Space Agency on the 07.06.2024.
Speaker: Diego Blas (IFAE/ICREA)
Title: Gravitational wave detection with orbital motion of Moon and artificial
Abstract:
In this talk I will describe some recent ideas to find gravitational waves from supermassive black holes or of primordial origin by studying their secular effect on the orbital motion of the Moon or satellites that are laser ranged.EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
Compexometric titration/Chelatorphy titration/chelating titration
Classification
Metal ion ion indicators
Masking and demasking reagents
Estimation of Magnisium sulphate
Calcium gluconate
Complexometric Titration/ chelatometry titration/chelating titration, introduction, Types-
1.Direct Titration
2.Back Titration
3.Replacement Titration
4.Indirect Titration
Masking agent, Demasking agents
formation of complex
comparition between masking and demasking agents,
Indicators/Metal ion indicators/ Metallochromic indicators/pM indicators,
Visual Technique,PM indicators (metallochromic), Indicators of pH, Redox Indicators
Instrumental Techniques-Photometry
Potentiometry
Miscellaneous methods.
Complex titration with EDTA.
JAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDS
The pathway(s) to seeding the massive black holes (MBHs) that exist at the heart of galaxies in the present and distant Universe remains an unsolved problem. Here we categorise, describe and quantitatively discuss the formation pathways of both light and heavy seeds. We emphasise that the most recent computational models suggest that rather than a bimodal-like mass spectrum between light and heavy seeds with light at one end and heavy at the other that instead a continuum exists. Light seeds being more ubiquitous and the heavier seeds becoming less and less abundant due the rarer environmental conditions required for their formation. We therefore examine the different mechanisms that give rise to different seed mass spectrums. We show how and why the mechanisms that produce the heaviest seeds are also among the rarest events in the Universe and are hence extremely unlikely to be the seeds for the vast majority of the MBH population. We quantify, within the limits of the current large uncertainties in the seeding processes, the expected number densities of the seed mass spectrum. We argue that light seeds must be at least 103 to 105 times more numerous than heavy seeds to explain the MBH population as a whole. Based on our current understanding of the seed population this makes heavy seeds (Mseed > 103 M⊙) a significantly more likely pathway given that heavy seeds have an abundance pattern than is close to and likely in excess of 10−4 compared to light seeds. Finally, we examine the current state-of-the-art in numerical calculations and recent observations and plot a path forward for near-future advances in both domains.
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...ABHISHEK SONI NIMT INSTITUTE OF MEDICAL AND PARAMEDCIAL SCIENCES , GOVT PG COLLEGE NOIDA
Microbial interaction
Microorganisms interacts with each other and can be physically associated with another organisms in a variety of ways.
One organism can be located on the surface of another organism as an ectobiont or located within another organism as endobiont.
Microbial interaction may be positive such as mutualism, proto-cooperation, commensalism or may be negative such as parasitism, predation or competition
Types of microbial interaction
Positive interaction: mutualism, proto-cooperation, commensalism
Negative interaction: Ammensalism (antagonism), parasitism, predation, competition
I. Mutualism:
It is defined as the relationship in which each organism in interaction gets benefits from association. It is an obligatory relationship in which mutualist and host are metabolically dependent on each other.
Mutualistic relationship is very specific where one member of association cannot be replaced by another species.
Mutualism require close physical contact between interacting organisms.
Relationship of mutualism allows organisms to exist in habitat that could not occupied by either species alone.
Mutualistic relationship between organisms allows them to act as a single organism.
Examples of mutualism:
i. Lichens:
Lichens are excellent example of mutualism.
They are the association of specific fungi and certain genus of algae. In lichen, fungal partner is called mycobiont and algal partner is called
II. Syntrophism:
It is an association in which the growth of one organism either depends on or improved by the substrate provided by another organism.
In syntrophism both organism in association gets benefits.
Compound A
Utilized by population 1
Compound B
Utilized by population 2
Compound C
utilized by both Population 1+2
Products
In this theoretical example of syntrophism, population 1 is able to utilize and metabolize compound A, forming compound B but cannot metabolize beyond compound B without co-operation of population 2. Population 2is unable to utilize compound A but it can metabolize compound B forming compound C. Then both population 1 and 2 are able to carry out metabolic reaction which leads to formation of end product that neither population could produce alone.
Examples of syntrophism:
i. Methanogenic ecosystem in sludge digester
Methane produced by methanogenic bacteria depends upon interspecies hydrogen transfer by other fermentative bacteria.
Anaerobic fermentative bacteria generate CO2 and H2 utilizing carbohydrates which is then utilized by methanogenic bacteria (Methanobacter) to produce methane.
ii. Lactobacillus arobinosus and Enterococcus faecalis:
In the minimal media, Lactobacillus arobinosus and Enterococcus faecalis are able to grow together but not alone.
The synergistic relationship between E. faecalis and L. arobinosus occurs in which E. faecalis require folic acid
Immersive Learning That Works: Research Grounding and Paths Forward
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
Summary Of transcription and Translation.pdf
Hello Everyone Here We are Sharing You with The process of protien Synthesis in very short points you will be Able to understand It Very well
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...
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Directdamage
Indirectly
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Kuramoto dynamics, glassy synchronization and rare regions in the human connectome - Pablo Villegas
- 1. Kuramoto dynamics, glassy synchronization and rare regions in the human connectome Pablo Villegas Quantitative Laws II (University of Granada)
- 2. The Kuramoto model Intrinsic frecuency · θi = ωi + k N j=1 Wijsin (θj − θi) + ηi (t) i = 1, ..., N Coupling term Noise z = reiψ = 1 N N j=1 eiθj Pablo Villegas | Kuramoto dynamics, glassy synchronization and rare regions in the human connectome 2/7
- 3. The Human Connectome Figure : Adjacency matrix and modular structure Pablo Villegas | Kuramoto dynamics, glassy synchronization and rare regions in the human connectome 3/7
- 4. The Human Connectome A hierarchical synchronization process appears, with local phase transitions and a new intermediate phase between order and disorder. Pablo Villegas | Kuramoto dynamics, glassy synchronization and rare regions in the human connectome 4/7
- 5. A model: Hierarchical Modular Network We can see the same phenomena in synthetic Hierarchic Modular Networks (HMNs), with local phase transitions and a bottom to up synchronization process. Pablo Villegas | Kuramoto dynamics, glassy synchronization and rare regions in the human connectome 5/7
- 6. Metastability in HMNs Switching behavior in the HC and HMNs. This behavior closely resembles ’up and down’ states. 200 400 600 800 0.3 0.5 0.7 0.3 0.5 0.7 0.3 0.5 0.7 HC(a) orderparameter (b) 0.2 0.3 0.4 0.2 0.3 0.4 20000 40000 60000 80000 time 0.2 0.3 0.4 HMN time 0 200 400 600 800 1000 time 0.20 0.22 0.24 0.26 0.28 0.30 orderparameter orderparameter(steady) (a) (b) 10−1 100 101 102 noise coeff. 0.200 0.205 0.210 0.215 0.220 0.225 0.230 Resonant peaks for some levels of intermediate noise in HMN networks. Perturbations lead the system to more coherent attractors in the intermediate phase. Pablo Villegas | Kuramoto dynamics, glassy synchronization and rare regions in the human connectome 6/7
- 7. Thanks for your attention Collaborators We acknowledge financial support from MINECO (National Plan of I+D+i), grant FIS2013-43201-P. Pablo Villegas | Kuramoto dynamics, glassy synchronization and rare regions in the human connectome 7/7