Large scale mass_distribution_in_the_illustris_simulationSérgio Sacani
Observations at low redshifts thus far fail to account for all of the baryons expected in the
Universe according to cosmological constraints. A large fraction of the baryons presumably
resides in a thin and warm–hot medium between the galaxies, where they are difficult to observe
due to their low densities and high temperatures. Cosmological simulations of structure
formation can be used to verify this picture and provide quantitative predictions for the distribution
of mass in different large-scale structure components. Here we study the distribution
of baryons and dark matter at different epochs using data from the Illustris simulation. We
identify regions of different dark matter density with the primary constituents of large-scale
structure, allowing us to measure mass and volume of haloes, filaments and voids. At redshift
zero, we find that 49 per cent of the dark matter and 23 per cent of the baryons are within
haloes more massive than the resolution limit of 2 × 108 M⊙. The filaments of the cosmic
web host a further 45 per cent of the dark matter and 46 per cent of the baryons. The remaining
31 per cent of the baryons reside in voids. The majority of these baryons have been transported
there through active galactic nuclei feedback. We note that the feedback model of Illustris
is too strong for heavy haloes, therefore it is likely that we are overestimating this amount.
Categorizing the baryons according to their density and temperature, we find that 17.8 per cent
of them are in a condensed state, 21.6 per cent are present as cold, diffuse gas, and 53.9 per cent
are found in the state of a warm–hot intergalactic medium.
Meridional brightness temperatures were measured on the surface of Titan during the 2004–2014 portion of the
Cassini mission by the Composite Infrared Spectrometer. Temperatures mapped from pole to pole during five twoyear
periods show a marked seasonal dependence. The surface temperature near the south pole over this time
decreased by 2 K from 91.7±0.3 to 89.7±0.5 K while at the north pole the temperature increased by 1 K from
90.7±0.5 to 91.5±0.2 K. The latitude of maximum temperature moved from 19 S to 16 N, tracking the subsolar
latitude. As the latitude changed, the maximum temperature remained constant at 93.65±0.15 K. In 2010
our temperatures repeated the north–south symmetry seen by Voyager one Titan year earlier in 1980. Early in the
mission, temperatures at all latitudes had agreed with GCM predictions, but by 2014 temperatures in the north were
lower than modeled by 1 K. The temperature rise in the north may be delayed by cooling of sea surfaces and moist
ground brought on by seasonal methane precipitation and evaporation.
Large scale mass_distribution_in_the_illustris_simulationSérgio Sacani
Observations at low redshifts thus far fail to account for all of the baryons expected in the
Universe according to cosmological constraints. A large fraction of the baryons presumably
resides in a thin and warm–hot medium between the galaxies, where they are difficult to observe
due to their low densities and high temperatures. Cosmological simulations of structure
formation can be used to verify this picture and provide quantitative predictions for the distribution
of mass in different large-scale structure components. Here we study the distribution
of baryons and dark matter at different epochs using data from the Illustris simulation. We
identify regions of different dark matter density with the primary constituents of large-scale
structure, allowing us to measure mass and volume of haloes, filaments and voids. At redshift
zero, we find that 49 per cent of the dark matter and 23 per cent of the baryons are within
haloes more massive than the resolution limit of 2 × 108 M⊙. The filaments of the cosmic
web host a further 45 per cent of the dark matter and 46 per cent of the baryons. The remaining
31 per cent of the baryons reside in voids. The majority of these baryons have been transported
there through active galactic nuclei feedback. We note that the feedback model of Illustris
is too strong for heavy haloes, therefore it is likely that we are overestimating this amount.
Categorizing the baryons according to their density and temperature, we find that 17.8 per cent
of them are in a condensed state, 21.6 per cent are present as cold, diffuse gas, and 53.9 per cent
are found in the state of a warm–hot intergalactic medium.
Meridional brightness temperatures were measured on the surface of Titan during the 2004–2014 portion of the
Cassini mission by the Composite Infrared Spectrometer. Temperatures mapped from pole to pole during five twoyear
periods show a marked seasonal dependence. The surface temperature near the south pole over this time
decreased by 2 K from 91.7±0.3 to 89.7±0.5 K while at the north pole the temperature increased by 1 K from
90.7±0.5 to 91.5±0.2 K. The latitude of maximum temperature moved from 19 S to 16 N, tracking the subsolar
latitude. As the latitude changed, the maximum temperature remained constant at 93.65±0.15 K. In 2010
our temperatures repeated the north–south symmetry seen by Voyager one Titan year earlier in 1980. Early in the
mission, temperatures at all latitudes had agreed with GCM predictions, but by 2014 temperatures in the north were
lower than modeled by 1 K. The temperature rise in the north may be delayed by cooling of sea surfaces and moist
ground brought on by seasonal methane precipitation and evaporation.
Bright features have been recently discovered by Dawn on Ceres, which extend
previous photometric and Space Telescope observations. These features should produce
distortions of the line profiles of the reflected solar spectrum and therefore an apparent
radial velocity variation modulated by the rotation of the dwarf planet. Here we report
on two sequences of observations of Ceres performed in the nights of 31 July, 26-
27 August 2015 by means of the high-precision HARPS spectrograph at the 3.6-m
La Silla ESO telescope. The observations revealed a quite complex behaviour which
likely combines a radial velocity modulation due to the rotation with an amplitude of
⇡ ±6 m s
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
1. A – Analyze Learners
General Character:
It is a classroom of 25 kindergarten students. There are 13 girls and 12 boys.
They are all in between the ages of 5 and 6. There are no significant physical
delays in any of the students. Four of the students speak English as a second
language and their families are from another country. There is a wide variety
of SES levels represented within the classroom. A few of the students show
early signs of a behavioral/attention deficit issue.
Specific Entry Competencies:
There is a wide spread of cognitive ability within the class. There are students
who are still having issues with their letters and others who are reading
chapter books.
Learning Style:
There are many different learning styles in the class. As many different
methods of teaching as possible are to be used to make sure students get as
much as they can from the unit.
S – State Objectives
Learning Outcomes:
Students will know what makes a ball a ball and be able to predict how
different balls will act when a uniform height. Also they will be able to use
nonstandard measurement. Students will follow directions and participate in
their group experiment. Students will be able to identify between a fair and
unfair test.
Conditions of Performance:
Students will actively participate in the experiment dropping different balls
from the same height and record how high it bounced and how many times.
Degree of Acceptable Performance:
Each student will participate and completely fill out their observation sheet.
All of the students will also practice using fair testing methods.
S – Select Methods, Media, Materials
Select Available Materials:
- Tables (as dropping point)
- Balls
2. -Computer
- Smart board
Design New Materials:
Create podcast and you tube video explaining what a fair test is.
Utilize Media and Materials
Preview Materials:
Make sure the YouTube video and podcast are up and running. Know about
how far the balls bounce to set up a good measuring scale.
Prepare Materials and Environment:
Set up all drop stations and measuring system for each.
Provide Learning Experience:
First the students will sit on the carpet and view the video and listen to the
podcast while everything is being set up. The children will be put in 8 groups
of 3 and go to the different drop stations and drop 8 different balls and record
how high it goes and how many times it bounces.
Require Learner Participation:
In-class and follow up and activities so learner can process information:
Each student will fill out a observation sheet where they will analyze the ball
and record how high it bounced and how many times.
Evaluate and Revise
Before, During, and After Instruction:
The majority of the evaluation will be observation during the experiment and
reviewing the observation sheets.
Assess Learner and Media Methods:
Media methods will be assessed by how students conduct the experiment,
whether its in a fair manner or not.
