Authored article
Ofsted's Chief Inspector, Sir Michael Wilshaw, introduces the 'Unknown children – destined for disadvantage?' report.
A child’s earliest years, from their birth to the time they reach statutory school age, are crucial. All the research shows that this stage of learning and development matters more than any other .
If we get the early years right, we pave the way for a lifetime of achievement. If we get them wrong, we miss a unique opportunity to shape a child’s future.
We know from the outcomes of Ofsted inspections that the overall quality of provision for this age group in England is better now than it has ever been. In March 2016, 86% of all registered early years providers (that is, nurseries, pre-schools and childminders) were judged as good or outstanding. That is a 14 percentage point increase in just 5 years. We are also finding that the quality of early years education in our primary schools is at least as high.
This raising of standards means that many more parents have a much better chance of finding a high-quality provider in their local area. At the same time, there are more children meeting the government’s standard of a ‘good level of development’ at the end of the Reception Year. In 2015, 66% of five-year-olds achieved this national expectation , an improvement of 15 percentage points since 2013. For many of these children, the future is likely to be promising.
The uncomfortable truth, however, is that although early education is better than it has ever been, it is still not benefiting our poorest children as much as their peers.
We know that nearly half of the children from disadvantaged backgrounds have not secured the essential knowledge, skills and understanding expected for their age by the time they finish Reception Year. Around a quarter are unable to communicate effectively, control their own feelings and impulses or make sense of the world around them to ensure that they are ready to learn.
Yet we also know that it is the poorest children who have the most to gain if they are given the opportunity to master these basic skills before they reach statutory school age – and the most to lose if they are not. By this point, the odds of these children catching up are stacked against them. In 2015, only 44% of children who had not reached the expected level at the age of 5 went on to securely achieve the national benchmark in reading, writing and mathematics at the age of 11. This compares with 77% of children who had achieved the good level of development.
One reason too many disadvantaged children get off to a bad start is that, in too many local areas, they are less likely to access high-quality early education.
In the most prosperous areas, only 8% of children are in early years provision that is less than good. For children living in the most deprived areas, this figure more than doubles, to 18% .
I commissioned ‘Unknown children – destined for disadvantage?’ to gain a better understanding of how local authorities, schools and registered early years providers were tackling the issue of disadvantage and lower standards for those children in the most deprived communities.
The role of local authorities is paramount. They are charged with meeting the needs of young children through the Childcare Act 2006 . This places a duty on councils to improve outcomes for all young children, reduce inequalities and ensure that there is sufficient, high-quality early years provision and childcare for parents locally.
All this demands joined-up thinking. When learning, development and health are so inextricably linked for the under-5s, tackling all forms of inequality should be integrated across the range of local children’s services.
This, in turn, requires strong and effective leadership at every level from the council cabinet to those leading early years provision.
When carrying out this survey, inspectors did indeed come across strong leaders who understood the importance of prioritising the early years. They were bringing services together to support disadvantaged families in a way that stood every chance of changing children’s destinies for the better. These leaders were removing the existing barriers between health and educational professionals that impeded them working together seamlessly and effectively.
One council had an elected member whose single designated responsibility was to address the needs of disadvantaged children. Unfortunately, this commitment was by no means widespread. More than half the local authorities we visited did not take a coordinated, strategic approach to tackling the issues faced by disadvantaged children and their families.
For too many councils, ensuring that pre-school children from poorer homes were being given a good start was low on their list of priorities. ‘They will catch up later’ was a common and complacent refrain that inspectors heard.
Even where a strategic plan was in place, around a third of those authorities did not have any specific targets or ambitions for improving the outcomes of disadvantaged children in the early years.
Inspectors encountered local authorities that were hampered by silo-working and unnecessary duplication of effort. Education and health teams within the same council did not know that the other was completing the same assessments for the same children. This poor information-sharing often stemmed from a culture of professional distrust across the different children’s services.
The government has introduced a number of recent measures to try to reduce levels of inequality and narrow the pre-school educational gap between disadvantaged and better off children. These include funded places for the most disadvantaged 2-year-olds and the new early years pupil premium for 3- and 4-year olds.
Local authorities have been handed responsibility for checking which children in their area are eligible for these different funding streams, as well as for directing the funding to early years providers in their area.
It is encouraging that there has been a 10 percentage point increase in the number of disadvantaged 2-year-olds taking up the government offer of free education since I highlighted this issue in my last early years annual report a year ago.
However, there were still around 80,000 children – nearly a third of all those eligible – whose families did not take up a funded place in 2015. That equates to a staggering £200 million worth of potential investment that has failed to reach the children for whom it is intended.
The situation is particularly bad in 2 local authority areas where the take-up of funded places for 2-year-olds was as low as 34%.
I am concerned that, as things stand, no one is being held to account for this scandalously poor performance. As a result, the opportunity to directly influence the future path of thousands of poorer children is being lost. Our survey found that the most effective local authority leaders had recognised that bureaucracy too often prevented funding getting to those that needed it most. They had, therefore, adapted national systems to make it easier for parents to access these entitlements. They were also working closely with schools and early years providers in their area to ensure that there was a sufficient number of high-quality places available in the most appropriate settings for disadvantaged children.
In other areas, however, local authority leaders said that finding enough early years providers willing to offer sufficient places for funded two-year-olds was a constant challenge. This was partly because many pre-school providers do not want to reduce the number of children whose parents pay a higher rate for their provision to accommodate a greater proportion of children on funded places that provide a lower return. Indeed, only 6 of the 27 nurseries and childminders we visited prioritised admission for funded or disadvantaged children. It was also partly because not enough primary school headteachers in their area were willing to show the necessary ambition or take the necessary steps to make this happen. Just five of the schools we visited were taking 2-year-olds into their early years classes, despite their premises often being situated in the most deprived parts of the borough.
This is worrying. As I have made clear before, I firmly believe that schools are best placed to lead on the necessary help needed by very young children from disadvantaged homes who are at risk of falling behind.
I say this because we know that a growing proportion of primary schools are already succeeding in reducing the disparity between poorer children and their peers in reading and other core skills between the ages of 5 and 7. They also have more access to specialist support and are better able to ensure a smooth transition into Reception from Nursery for those children who often find it a struggle to adapt to new routines and a new environment.
Schools have already been given the right to prioritise the poorest children when drawing up their admissions criteria. Furthermore, bureaucracy on schools has been reduced: they are no longer required to register separately with Ofsted to take 2-year-olds.
However, it is clear from our survey that obstacles still remain. While in some places, school leaders are stepping up to the plate in increasing numbers, there was a notable reluctance in other areas to do so.
In some local authorities, leaders were thinking of increasingly creative and flexible ways to encourage and incentivise more headteachers to take funded two-year-olds and disadvantaged 3-year-olds. One council, for example, was providing a top-up to hourly funding as well as free training for staff and a one-off ‘start-up’ fee to help providers purchase new equipment or reorganise the learning environment.
It is clear from our survey that some local authorities, schools and early years settings are making effective use of the funding available to them to give poorer children the good start they so desperately need. Strong leaders at the town hall level, as well as in individual schools and settings, are demonstrably strategic, innovative and committed to making a difference.
However, there was a discernible lack of such ambition in a number of the local authorities we visited. Any potential for improving the prospects of the most disadvantaged young children was too often thwarted by weak leadership, ineffective managerial oversight, duplication and inefficiency. In these councils, government funding was not being used in a sufficiently targeted, coordinated way to make a difference.
It is clear from our findings that action is needed on a national and local level to address these variations and to ensure that the weakest places learn from the best. Early education has the potential to drive social mobility and improve outcomes for the next generation. We should not let them down.
Sir Michael Wilshaw
Published: 14 July 2016
From: Ofsted Sir Michael Wilshaw
Part of: HMCI's monthly commentaries


{% extends "layout.html" %} {% block content %}
Index Sequence Constraints are built from Allen's interval algebra to describe locational constraints between the intervals of biopolymers. Index Sequence Constraints do not describe constraints with biopolymer strandedness in mind. To describe constraints which work with stranded components see Topological Sequence Constraints
This constrains that A and B contain the same start and end positions.
The 'contains' constraint aswell as the 'within' constraint are the supersets of the 'equals', 'ends_with' and 'starts_with' constraints. This constrains that B must have a start point >= to the start point of A and have an end point <= to the end point of A .
Example: SpaR contains RBS_Spak
This constrains that A must have a start point >= to the start point of B and an end point <= to the end point of B.
Example: SpaR within Spark_Operon
This constrains that the end points of A and B are equal and that the start point of B > than the start point of A.
Example: SpaK ends_with double_stop_codon
This constrains that the start point of A and B are equal and that the end point of B is < than the end point of A.
Example: SpaK starts_with ATG_startcodon
This constrains that the end point of A is touching the start point of B. The start point of B is equal to the end point of A + 1
Example: BBa_k174008 touches GFP , GFP touches SMTA . A protein fusion example.
This constrains that the both the start and end point of A are < than then start and end point of B. The start point of B is equal to the end point of A + i where i = 2,3,4,...,n.
Example: ProD gap_then bba_B0032 . Davis et al.
The 'then' constraint is the superset of 'gap_then' and 'touches'. It describes that A comes before B but does not specify if there is a gap or if they are touching.
This constrains that the end of A overlaps with the start of B. The start point of A is < than the start point of B. The end point of A is >= to the start point of B and is < than the end point of B.
Example: RockR_promotor overlaps RockR binding site
{% endblock %}


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Dark City (*** 1/2 out of four)
Written and Directed by Alex Proyas Starring Rufus Sewell, William Hurt, Kiefer Sutherland, Jennifer Connelly
Dark City is such a rare treat: itıs a stunning, hyperkinetic vision of a place where our reality is fused with noir, science fiction and the darkest nights in Manhattan and London. To boot, it is accompanied by an intense, well written and thoughtful story. Movies of this caliber and idea arenıt made too often, and itıs unfortunate that I waited this long to see it. Alex Proyas, whoıs previous film The Crow looked good but couldnıt cover up the terrible acting or story, here shows a near masterpiece; a combination of Metropolis, Edward Hopper and Phillip Marlowe, fused seemlessly. At times it moves beyond film into artwork.
It is the story of ³strangers², aliens from another planet (and we know theyıre aliens because they shave their heads and wear overcoats one of the detractions of the film) who experiment on humans to discover what makes them live, what makes up our ³soul². These aliens are superior to humans because they have mastered the ³ultimate technology² of shaping matter with their mind, called ³tuning. They are aided by a human scientist, played by Kiefer Sutherland, who has ³betrayed his kind² and at the start of the film watches as the entire city stops at exactly midnight. During this time, John Murdoch, played swiftly by Rufus Sewell, wakes in a bathtub in a room with a swinging overhead light (a terrific visual effect - not only is Murdoch confused, but so is the audience). Without a memory and a strange guilt that he may be a killer, he receives a phone call to flee, as the strangers are after him.
I donıt want to proceed to much further with the explanation of the story; One of the pleasures of the film is watching it develop, in a way regaining Murdochıs ³identity² along with him. Itıs a pleasure to watch the characters develop through the cinematography. Murdochıs wife, Anna, is introduced through a stunning beam of light: she is a lounge singer who sings into a bright spotlight. Shadows, outlines of men in hats watch, as she gently curves through the shine. We see the outline of her body from behind, an hourglass, as she sings a slow, rhythmic song. A great entrance.
However, a film such as this is only successful if the morals and themes behind it are strong enough to leave the viewer satisfied. The city is nice to look at, but if itıs a poor story then itıs not worth watching. Blade Runner was popular not only because itıs visuals, but itıs story and themes were thought out and provoked strong response from the audience. It is discussed it and argued, therefore a success. Other science fiction films of recent times, such as the Fifth Element, are nice to look at, but are dropped and forgotten because the cookie cutter moral behind them is so flimsy. Weıre left with ³love conquers all² after finishing the Fifth Element. Dark City is not so easily explained away. As the strangers discovered, locating the human soul and discovering what makes us survive is not such an easy task. Where is reality?
Dark City is certainly the best science fiction film of the 90ıs, and ranks along with the best made in the 80s, such as Blade Runner and the two Aliens films. Perhaps itıs the best of the both decades; it had the darkness of the Aliens films, as well as the visuals and compelling story of Blade Runner, but moved beyond, I think, because the themes behind it were much stronger. Anyone who wants to make an argument for better science fiction films please feel free to write, Iıd love to hear it.
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He who would cross the Bridge of Death Must answer me These questions three Ere the other side he see.


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By: Arina, Eric, and Victor
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This presentation is navigated through the arrows in the bottom right corner of the screen.
Within each section, vertical arrows such as the ones on this slide will be shown. This means that there are vertical slides available to expand on a certain pages content. This is how you navigate each section.
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This web-based presentation is the final documentary project for IMD4002A.
It covers the history and advancements made in 3D environments and CGI in media, as well as how these developments have impacted culture as we know it.
Through this presentation, we aim to answer the following questions:
In this section, we cover the origin of Virtual Environments and some of their early applications.
A Virtual Environment is defined as "A central interface the software that creates an interactive and immersive experience for administrators and users".
Can you guess what the most common applicaton of 3D virtual environments are?
1960's : Electro-mechanical games called Periscope and Crown Special Soccer within arcade environments.
1970's - 1980 : Atari releases multiple games and take the gaming world by storm, allowing for virtual arcade integration into bars, malls, etc.
- This now meant that virtual environments could have both entertainment and social value within gaming/social cultures.Early 1980's : The personal computer is introduced allowing creating potential for the internet and networked collaboration through software systems.
Take a look at the video HERE.
This video, highlighting a mirade of arcade environments from the 1980's, is a good example as to how popular these virtual interactions were.
These arcades provided:
As evident throughout history, video games and their interactive environments led to entertainment for the masses!
As clearly evident by this graph, demand for video games has nearly always been able to keep up pace with the amount released. We see a particularly large spike towards the mid 2000's in both interest and demand.
Surely, arcades alone can't be responsible for this growth right?
The year was 1982, and TIME Magazine took a contravercial stance by choosing a "machine of the year", rather than a "man of the year".
Their yearly piece came out at a time when PC sales were rapidely increasing, dubbing the timeframe a name of: "The PC Revolution!"
This title properly fit the time period due to the crazy sales numbers of personal PC computers.
In 1982, over 3 million units were sold!
Now a days, the internet can seem like a scary place, but the internet started out as a military project in the late 20th century. When the web turned open source, the internet introduced the world to a land of virtual connectivity!
Suddenly, the possibility of virtual multiplayer games and conjoined interconnected systems became a very real possibility.
Some of the earliest online games include:
In this section, we covered just some of the ways 3D technology and an interest in its first advancements were sparked within our culture. From the first video game consoles where in-person multiplayer became possible, to the first personal computers coming out and opening up a world of interconnected opportunity, we see these events impacts in our daily lives.
Click the RIGHT arrow to advance to the next section.
In this section, we will delve into the history of one of the most intriguing 3D environments we have available to us today.
Virtual Reality:
The computer-generated simulation of a three-dimensional image or environment that can be interacted with in a seemingly real or physical way by a person using special electronic equipment, such as a helmet with a screen inside or gloves fitted with sensors.
Now, in the 21st century, we commonly see virtual reality headsets and large game companies come out with games solely tailored for their use.
But, where did these decives start? For that answer, we need to go back to the mid 20th century to a cinematographer named ...
Morton Heilig, a cinematographer, created the first virtual reality experience for public consumption called “Sensorama". It resembled a mix between an eye exam machine and a photobooth. There were 6 short films created where users would be bombarded with stimuli at certain points in the presentations.
This relatively primative device was the first publically available virtual reality experience!
Later into the 1960's, Morton Heilig was at it again, creating what one of the worlds first head-mounted masks!
This mask coined the name of "The Telesphere Mask" and contained wide-vision, sterio quality sound and adjustable components to better fit a users head!
Some modern VR headsets can't even manage that!
It is safe to say that Morton Heilig set the stage for advanced Virtual Reality technology to become a reality.
As we moved through the 1960's, we see the military take particular interest in head tracking and flight training implementations of this technology.
Two engineers named Comeau and Bryan created the first motion tracking head mounted display with built in video screens for each eye and a head tracking system.
This was not virtual reality however. It allowed to look at remote, hazardous situations. A remote camera imitated the head movements so the user could look around the setting.
In 1965, the scientist Ivan Sutherland, presented his vision of the "Ultimate Display". The concept was of a virtual world viewed through an HMD which replicated reality so well that the user would not be able to differentiate from actual reality.
“The ultimate display would, of course, be a room within which the computer can control the existence of matter. A chair displayed in such a room would be good enough to sit in. Handcuffs displayed in such a room would be confining, and a bullet displayed in such a room would be fatal. With appropriate programming such a display could literally be the Wonderland into which Alice walked.”
In 1966, Military engineer Thomas A. Furness III created a flight simulator. It was created specifically for training purposes for the U.S. Air Force
This project was specifically valuable to the evolution of this kind of technology due to the amount of funding provided by the U.S. military.
Moving forward to the mid 1970's, the first interactive virtual reality platform was created. It was displayed at the Milwaukee Art Center and dubbed the name "VIDEOPLACE".
The simplistic system used a combination of cameras, projectors and sensors to generate silhouettes that immitate a users actions.
VIDEOPLACE set a precedent for what interactive systems were possible with virtual reality.
Moving through the 1980's and into the early 1990's, we see a VR system released to drive the Mars Rover called Virtuality. These were the first mass-produced VR systems.
This initial invention showed the public the gaming industry was a viable domain for virtual reality technology.
Unfortunately, the device never really took off and is known as an innovative VR device created two decades too early.
The most common type of VR innovation through the majority of the 1990's were large game companies taking cracks at developing gaming headsets.
Some of these companies include:
Virtual Reality innovation took a back seat to tradition media with the introduction of advanced cell phones, larg-scale internet services and big-screen televisions. Suddenly, there was no real interest in virtual reality innovation from a consumer stand-point.
Between 2000 and 2010, we see a real shortage of game-related Virtual Reality integration into tech markets. Instead, large companies such as Google move towards practical implementation of VR technologies.
Google implements two technologies. Google Street-View and Stereoscopic 3D Street View from 2007 to 2010.
These technologies proved to users worldwide how virtual reality could be implemented into their daily lives.
Check out this video to learn about its current state.
2012 marked the start of the return in the VR gaming industry. The launch of the Oculus Rift Kickstarter and its purchase by Facebook for over 2 Billion dollars in 2014 was a verificational stamp of approval for the resurgence of VR gaming.
By 2016 hundreds of companies were developing VR products. Most of the headsets had dynamic binaural audio.
Most gaming headsets used a combination of touch and haptic interfaces.
Companies leading the charge while developing their own VR headsets indlue: HTC, Google, Apple, Amazon, Microsoft Sony, Samsung
In this section, we delved into the roots of Virtual Reality, its realted integrations into society and some reasons as to why it was pushed to the side in the past.
Click the RIGHT arrow to advance to the next section.
In this section, we will discuss CGI and virtual environments are used in todays modern world.
In recent years, CGI has been the go-to visual effect for most major movies, whether its use is subtle or obvious.
So this begs the question, what is CGI exactly?
To put it simply, CGI is the application of the field of 3D computer graphics to special effects in film, television, video games, etc.
CGI is a rather advanced topic. It combines 2D imagery (objects, background, environments) width 3D objects within specialized computer programs. When done properly, it creates composite imagery that ticks the eye into believing in the illusion depicted.
Here are some great examples of how 3D computer graphics is used to add fictional characters, create backgrounds, change the mood and completely overhaul a scene.
CGI has become synonymous with massive tent-pole blockbuster films such as Avatar, Interstellar, Avengers: Endgame. However, where CGI becomes truly impressive is when it's used as the "supporting act".
With the ability to edit every single pixel of a movie, filmmakers can take a more subtle root to enhance their films in ways previously unobtainable.
The beauty is that CGI can be used to help remove unwanted backgrounds, change the mood of a scene, fix errors, change locations and even add a tear to help improve an actors performance.
Here are some examples of how CGI has been used in run-of-the-mill scenes:
Here are some examples of how CGI has been used in run-of-the-mill scenes:
The art of computer graphics is extremely technical and requires teams with hundreds, often thousands of highly skilled artists. The problem is that as CGI improves in movies, so do the viewers.
Viewers become critics and can start picking out CGI that is not perfect and scream for the skies and make sure everyone hears it.
The good news is that studios have - for the most part - realised that story is king, not CGI. Computer graphics is there as a tool to tell a story and it should never be the reason for creating a film in the first place.
Now, while we have realized CGI does not make a good media piece, we know for certain is can ruin one if implemented poorly.
Click the following links to view some examples of very poorly implemented CGI:
In this section, we conducted a comprehensive analysis of what CGI is, what it is used for and why it is valueable to our society. Overall it is an incredible advancement in modern media and provides a plethora of entertainment value.
Click the RIGHT arrow to advance to the next section.
In this section, we will discuss ways modern graphics technology integration into society creates complex challenges for our culture. In particular, "The Uncanny Valley".
For this section, there are pleanty of areas we could focus on. For this particular research project, we have chosen to emphasize a concept known as: The Uncanny Valley
The Uncanny Valley was a term first coined by a professor by the name of Masahiro Mori during the 1970’s. It correlates to the relationship between the reaction’s humans feel when interacting with realistic versus non-realistic humanoid robots.
In a more realistic looking humanoid robot, often people would be left feeling creeped out and would provoke an uncanny feeling within them.
The phenonemnon of the uncanny valley is ever present in most production level media forms we consume today.
We see examples of the uncanney valley within Film, Television, and on internet media sources. Anything that triggers that "uneasy" feeling while comparing real world event to CGI comparables.
Potential problems lay within the idea that a realistic humanoid robot's could eventually become indestinguishable from a real life human being.
This opens the door for issues such as impersonations leading to social issues within our delicate western social fabrics.
Deepfakes are a type of output produced when artificial intelligence and deep learning are utilized to create realistic digital versions of events, interactions and human behaviour.
Likely areas of deepfake use include:
Socially, as deepfakes become more and more prevelent on online resources, they can raise numerous red flags in terms of social and cultural threat potential.
Some threats could include:
As you can see, the uncanny valley saves us from believing fake depictions of our leaders, public figures, and loved ones are a reality.
This concept of an uncanny valley can be integrated into computer generated interfaces as well. In this medium, it would refer to when a photorealistic environment does not feel "exactly" right and does not conform to how we characterize the physical world in our lives.
The main question regarding the uncanny valley and all its implications is the question of will it exist in the future?
Take a look at this image. Can you tell which side is real and which side is pure CGI?
This is just one example of how the uncanny valley can be very hard to distinguish within modern applications of CGI.
As we advance CGI technologies, we have started to see the uncanney valley narrow and nearly dissapear in several instances of CGI interpolations.
Some CGI artists and high profile industry professionals believe it is important for us to be able to tell the difference between real world events and CGI events for artistic, social, and cultural balance.
We should enjoy media as an entertainment medium and not run the risk of it being leveraged to cause harm.
In this section, we took a look at how CGI and its modern implementations (specifically the effect of the uncanny valley) could have adverse effects on populations throughout the modern world. We touched on cause and effect relationships and depicted how closely CGI humans can appear to being real-world.
Click the RIGHT arrow to advance to the next section.


Each node of the refinement tree corresponds to an element that occurred during the grid refinement process. The first level of the tree (the children of the root of the tree) corresponds to the initial coarse grid, one tree node per initial element. It is assumed that the initial coarse grid does not change through the execution of the program, except that the local IDs, assignment of elements to processors, and weights can change. If any other aspect of the coarse grid changes, then the Zoltan structure should be destroyed and recreated. The children of a node in the tree correspond to the elements that were created when the corresponding element was refined. The children are ordered such that a traversal of the tree creates a space-filling curve within each initial element. If the initial elements can be ordered with a contiguous path through them, then the traversal creates a space-filling curve through all the elements. Each element has a designated "in" vertex and "out" vertex, with the out vertex of one element being the same as the in vertex of the next element in the path, in other words the path goes through a vertex to move from one element to the next (and does not go out the same vertex it came in).
The user may allow Zoltan to determine the order of the coarse grid elements, or may specify the order, which might be faster or produce a better path. If Zoltan determines the order, the user can select between an order that will produce connected parts, an order based on a Hilbert Space Filling Curve, or an order based on a Sierpinski Space Filling Curve. See the parameter REFTREE_INITPATH below. If the user provides the order, then the in/out vertices must also be supplied. Similarly, the user may specify the order and in/out vertices of the child elements, or allow Zoltan to determine them. If the user knows how to provide a good ordering for the children, this may be significantly faster than the default general algorithm. However, accelerated forms of the ordering algorithm are provided for certain types of refinement schemes and should be used in those cases. See ZOLTAN_CHILD_LIST_FN. If the user always specifies the order, then the vertices and in/out vertices are not used and do not have to be provided.
Weights are assigned to the nodes of the tree. These weights need not be only on the leaves (the elements of the final grid), but can also be on interior nodes (for example, to represent work on coarse grids of a multigrid algorithm). The default weights are 1.0 at the leaves and 0.0 at the interior nodes, which produces a partition based on the number of elements in each part. An initial tree traversal is used to sum the weights, and a second traversal to cut the space-filling curve into appropriately-sized pieces and assign elements to parts. The number of parts is not necessarily equal to the number of processors.
The following limitations should be removed in the future.
Another limitation is that refinement tree partitioning has not been modified to work with
64-bit global IDs. If 64-bit IDs are selected at configure time with either the
autotools build or the
CMake build, the method will fail.
| Method String: | REFTREE |
| Parameters: | |
| REFTREE_HASH_SIZE | The size of the hash table to map from global IDs to refinement tree nodes. Larger values require more memory but may reduce search time. |
| Default: | |
| REFTREE_HASH_SIZE = 16384 | |
| REFTREE_INITPATH | Determines the method for finding an order of the elements in the initial grid. "SIERPINSKI" uses a Sierpinski Space Filling Curve and is most appropriate for grids consisting of triangles. It is currently limited to 2D. "HILBERT" uses a Hilbert Space Filling Curve and is most appropriate for grids consisting of quadralaterals or hexahedra. "CONNECTED" attempts to produce connected parts (guaranteed for triangles and tetrahedra), however they tend to be stringy, i.e., less compact than the SFC methods. It is most appropriate when connected parts are required. An invalid character string will invoke the default method. |
| Default: | |
| REFTREE_INITPATH = "SIERPINSKI" if the grid contains only triangles REFTREE_INITPATH = "HILBERT" otherwise NOTE: In Zoltan versions 1.53 and earlier the default was "CONNECTED". To reproduce old results, use REFTREE_INITPATH = "CONNECTED". | |
| Required Query Functions: | |
| ZOLTAN_NUM_COARSE_OBJ_FN | |
| ZOLTAN_COARSE_OBJ_LIST_FN or ZOLTAN_FIRST_COARSE_OBJ_FN/ZOLTAN_NEXT_COARSE_OBJ_FN pair | |
| ZOLTAN_NUM_CHILD_FN | |
| ZOLTAN_CHILD_LIST_FN | |
| ZOLTAN_CHILD_WEIGHT_FN | |
| The following functions are needed only if the order of the initial elements will be determined by a space filling curve method: | |
| ZOLTAN_NUM_GEOM_FN | |
| ZOLTAN_GEOM_MULTI_FN or ZOLTAN_GEOM_FN | |


Your $component is NOT working. It has a current of $current flowing through it. $bulbInfo $resistanceInfo $cellInfo The $component is $functionOfVoltage $voltage.


The Family Man is an edgy action-drama series, which tells the story of a middle-class man who works for a special cell of the National Investigation Agency (NIA) . While he tries to protect the nation from terrorists, he also has to protect his family from the impact of his secretive, high-pressure, and low paying job. One of the most appealing parts about ‘The Family Man’ is that it’s a kind of thriller, but has interesting modern-day relationship dynamics like spying on your wife and who’s she going to meet for lunch … etc.,
As it is based on a series of actual terrorist activities that ripped India over the years, 'The Family Man' is a grim and sobering spy thriller series.
Also, Samantha Akkineni, a massive star in South India, is likely to appear in the second season of 'The Family Man'. The actress or the show's creators are yet to confirm the rumour.
Game of Thrones is an American fantasy drama television series which premiered on 17 April 2011, and is produced by the HBO cable network. It is based on the medieval fantasy novel series “A Song of Ice and Fire” by George R.R. Martin. The Game of Thrones TV series was created by David Benioff and D.B. Weiss. Production of the series is based in the capital of Northern Ireland, Belfast. The award-winning television series is the largest and most expensive television production that Northern Ireland has ever produced. In 2015, the Game of Thrones TV show set the record of winning most Emmys in a single year with 12 wins out of 24 nominations.
The plot in the Game of Thrones television series concerns the strife between the seven noble families and various other factions fighting and conspiring against each other to gain control of the Iron Throne of Westeros. With Kings and Queens, knights and renegades, liars and honest men, lords and holy men all vying for power, oblivious of the dark forces that lie beyond an 800-foot wall of solid ice in the frozen north, watch as things unfold and shatter expectations in this epic fantasy series. Hotstar offers you the best experience for watching Game of Thrones online, unspoiled and minutes after America.
Newcomer Katherine Langford plays the role of Hannah, a young woman who takes her own life. Two weeks after her tragic death, a classmate named Clay finds a mysterious box on his porch. Inside the box are recordings made by Hannah -- on whom Clay had a crush -- in which she explains the 13 reasons why she chose to commit suicide. If Clay decides to listen to the recordings, he will find out if and how she made the list. This intricate and heart-wrenching tale is told through Clay and Hannah's dual narratives.
Breathe is an Indian drama that explores the lives of ordinary men faced with extraordinary circumstances. Kabir (Sadh), a brilliant but non-conventional officer of the Crime Branch, puts the pieces together of seemingly unconnected deaths of organ donors that lead up to an unlikely suspect - the affable Danny (Madhavan). Kabir will not stop till he cracks the case and delivers justice.
The main plot of the series just asks one question – how far will you go to protect the one you love. Two desperate and driven men must engage in the ultimate cat and mouse game to save the one they love.
Lust Stories is a 2018 Indian anthology film, consisting of four short film segments. Lust Stories delightfully pushes boundaries to tell real stories about real women, who are unapologetic in their imperfections and desires, and go about mending their heart strings the best they can. Lust after all, is never too far from the other L-word.
Sacred Games is an Indian web television thriller series based on Vikram Chandra's 2006 novel of the same name. The first Netflix original series in India. Sartaj Singh (Saif Ali Khan) is a troubled police officer in Mumbai who receives a phone call from gangster Ganesh Gaitonde (Nawazuddin Siddiqui), who tells him to save the city within 25 days. The series chronicles the events that follow. Amidst the chaos, trappings of a corrupt underworld are revealed. After being removed from the Gaitonde case, Singh begins his own investigation as he works to save Mumbai from impending doom. Flashbacks reveal some of the crimes that Gaitonde has committed through the years.
Karenjit Kaur – the untold story of Sunny Leone is a ZEE5 Original Web Series. The series captures the journey of former pornstar-turned-actor Sunny Leone, born as Karenjit Kaur in a middle-class Sikh family, and her makeover from being an innocent girl to an adult film actress and eventually a Bollywood star.
The series reveals her history, family, boyfriend-turned-husband Daniel Webber and traces lesser-known facts about her transformation from an adult film star to a popular mainstream actress. Sunny Leone has been a controversial figure for Indian masses. The actress has a massive fan-following across the world. But she became a trend-setter of sorts by effortlessly making her way from computer screens to dinner-table conversations in many a household, even in traditional and small-town India.
A group of young friends witness supernatural forces and secret government exploits. As they search for answers, the children unravel a series of extraordinary mysteries.
Mirzapur is an Indian crime thriller web Indian television series. It revolves around drugs, guns and lawlessness. It depicts the putrescence, governance and rule of mafia dons and the rivalry and crime prevailing in the Purvanchal region of Uttar Pradesh.
The iron-fisted Akhandanand Tripathi is a millionaire carpet exporter and the mafia don of Mirzapur. His son, Munna, is an unworthy, power hungry heir who will stop at nothing to inherit his father’s legacy. An incident at a wedding procession forces him to cross paths with Ramakant Pandit, an upstanding lawyer, and his sons, Guddu and Bablu.
Friends is an American television sitcom (situation comedy) show revolved around six friends in their 20s and 30s who lived in Manhattan, New York City. The lives of six reckless adults living in Manhattan, indulge in adventures which make their lives both troublesome and happening.


ir_datasets
: MedlineMedical articles from Medline. This collection was used by TREC Genomics 2004-05 (2004 version of dataset) and by TREC Precision Medicine 2017-18 (2017 version).
3M Medline articles including titles and abstracts, used for the TREC 2004-05 Genomics track.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2004")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, title, abstract>
You can find more details about the Python API here.
ir_datasets export medline/2004 docs
[doc_id] [title] [abstract]
...
You can find more details about the CLI here.
import pyterrier as pt
pt.init()
dataset = pt.get_dataset('irds:medline/2004')
# Index medline/2004
indexer = pt.IterDictIndexer('./indices/medline_2004')
index_ref = indexer.index(dataset.get_corpus_iter(), fields=['title', 'abstract'])
You can find more details about PyTerrier indexing here.
The TREC Genomics Track 2004 benchmark. Contains 50 queries with article-level relevance judgments.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2004/trec-genomics-2004")
for query in dataset.queries_iter():
query # namedtuple<query_id, title, need, context>
You can find more details about the Python API here.
ir_datasets export medline/2004/trec-genomics-2004 queries
[query_id] [title] [need] [context]
...
You can find more details about the CLI here.
import pyterrier as pt
pt.init()
dataset = pt.get_dataset('irds:medline/2004/trec-genomics-2004')
index_ref = pt.IndexRef.of('./indices/medline_2004') # assumes you have already built an index
pipeline = pt.BatchRetrieve(index_ref, wmodel='BM25')
# (optionally other pipeline components)
pipeline(dataset.get_topics('title'))
You can find more details about PyTerrier retrieval here.
Language: en
Note: Uses docs from medline/2004
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2004/trec-genomics-2004")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, title, abstract>
You can find more details about the Python API here.
ir_datasets export medline/2004/trec-genomics-2004 docs
[doc_id] [title] [abstract]
...
You can find more details about the CLI here.
import pyterrier as pt
pt.init()
dataset = pt.get_dataset('irds:medline/2004/trec-genomics-2004')
# Index medline/2004
indexer = pt.IterDictIndexer('./indices/medline_2004')
index_ref = indexer.index(dataset.get_corpus_iter(), fields=['title', 'abstract'])
You can find more details about PyTerrier indexing here.
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | not relevant |
| 1 | possibly relevant |
| 2 | definitely relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2004/trec-genomics-2004")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export medline/2004/trec-genomics-2004 qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
import pyterrier as pt
from pyterrier.measures import *
pt.init()
dataset = pt.get_dataset('irds:medline/2004/trec-genomics-2004')
index_ref = pt.IndexRef.of('./indices/medline_2004') # assumes you have already built an index
pipeline = pt.BatchRetrieve(index_ref, wmodel='BM25')
# (optionally other pipeline components)
pt.Experiment(
[pipeline],
dataset.get_topics('title'),
dataset.get_qrels(),
[MAP, nDCG@20]
)
You can find more details about PyTerrier experiments here.
Bibtex:
@inproceedings{Hersh2004TrecGenomics, title={TREC 2004 Genomics Track Overview}, author={William R. Hersh and Ravi Teja Bhuptiraju and Laura Ross and Phoebe Johnson and Aaron M. Cohen and Dale F. Kraemer}, booktitle={TREC}, year={2004} }The TREC Genomics Track 2005 benchmark. Contains 36 queries with passage-level relevance judgments.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2004/trec-genomics-2005")
for query in dataset.queries_iter():
query # namedtuple<query_id, text>
You can find more details about the Python API here.
ir_datasets export medline/2004/trec-genomics-2005 queries
[query_id] [text]
...
You can find more details about the CLI here.
import pyterrier as pt
pt.init()
dataset = pt.get_dataset('irds:medline/2004/trec-genomics-2005')
index_ref = pt.IndexRef.of('./indices/medline_2004') # assumes you have already built an index
pipeline = pt.BatchRetrieve(index_ref, wmodel='BM25')
# (optionally other pipeline components)
pipeline(dataset.get_topics())
You can find more details about PyTerrier retrieval here.
Language: en
Note: Uses docs from medline/2004
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2004/trec-genomics-2005")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, title, abstract>
You can find more details about the Python API here.
ir_datasets export medline/2004/trec-genomics-2005 docs
[doc_id] [title] [abstract]
...
You can find more details about the CLI here.
import pyterrier as pt
pt.init()
dataset = pt.get_dataset('irds:medline/2004/trec-genomics-2005')
# Index medline/2004
indexer = pt.IterDictIndexer('./indices/medline_2004')
index_ref = indexer.index(dataset.get_corpus_iter(), fields=['title', 'abstract'])
You can find more details about PyTerrier indexing here.
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | not relevant |
| 1 | possibly relevant |
| 2 | definitely relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2004/trec-genomics-2005")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export medline/2004/trec-genomics-2005 qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
import pyterrier as pt
from pyterrier.measures import *
pt.init()
dataset = pt.get_dataset('irds:medline/2004/trec-genomics-2005')
index_ref = pt.IndexRef.of('./indices/medline_2004') # assumes you have already built an index
pipeline = pt.BatchRetrieve(index_ref, wmodel='BM25')
# (optionally other pipeline components)
pt.Experiment(
[pipeline],
dataset.get_topics(),
dataset.get_qrels(),
[MAP, nDCG@20]
)
You can find more details about PyTerrier experiments here.
Bibtex:
@inproceedings{Hersh2005TrecGenomics, title={TREC 2005 Genomics Track Overview}, author={William Hersh and Aaron Cohen and Jianji Yang and Ravi Teja Bhupatiraju and Phoebe Roberts and Marti Hearst}, booktitle={TREC}, year={2007} }26M Medline and AACR/ASCO Proceedings articles including titles and abstracts. This collection is used for the TREC 2017-18 TREC Precision Medicine track.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2017")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, title, abstract>
You can find more details about the Python API here.
ir_datasets export medline/2017 docs
[doc_id] [title] [abstract]
...
You can find more details about the CLI here.
import pyterrier as pt
pt.init()
dataset = pt.get_dataset('irds:medline/2017')
# Index medline/2017
indexer = pt.IterDictIndexer('./indices/medline_2017')
index_ref = indexer.index(dataset.get_corpus_iter(), fields=['title', 'abstract'])
You can find more details about PyTerrier indexing here.
The TREC Precision Medicine (PM) Track 2017 benchmark. Contains 30 queries containing disease, gene, and target demographic information.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2017/trec-pm-2017")
for query in dataset.queries_iter():
query # namedtuple<query_id, disease, gene, demographic, other>
You can find more details about the Python API here.
ir_datasets export medline/2017/trec-pm-2017 queries
[query_id] [disease] [gene] [demographic] [other]
...
You can find more details about the CLI here.
import pyterrier as pt
pt.init()
dataset = pt.get_dataset('irds:medline/2017/trec-pm-2017')
index_ref = pt.IndexRef.of('./indices/medline_2017') # assumes you have already built an index
pipeline = pt.BatchRetrieve(index_ref, wmodel='BM25')
# (optionally other pipeline components)
pipeline(dataset.get_topics('disease'))
You can find more details about PyTerrier retrieval here.
Language: en
Note: Uses docs from medline/2017
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2017/trec-pm-2017")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, title, abstract>
You can find more details about the Python API here.
ir_datasets export medline/2017/trec-pm-2017 docs
[doc_id] [title] [abstract]
...
You can find more details about the CLI here.
import pyterrier as pt
pt.init()
dataset = pt.get_dataset('irds:medline/2017/trec-pm-2017')
# Index medline/2017
indexer = pt.IterDictIndexer('./indices/medline_2017')
index_ref = indexer.index(dataset.get_corpus_iter(), fields=['title', 'abstract'])
You can find more details about PyTerrier indexing here.
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | not relevant |
| 1 | possibly relevant |
| 2 | definitely relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2017/trec-pm-2017")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export medline/2017/trec-pm-2017 qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
import pyterrier as pt
from pyterrier.measures import *
pt.init()
dataset = pt.get_dataset('irds:medline/2017/trec-pm-2017')
index_ref = pt.IndexRef.of('./indices/medline_2017') # assumes you have already built an index
pipeline = pt.BatchRetrieve(index_ref, wmodel='BM25')
# (optionally other pipeline components)
pt.Experiment(
[pipeline],
dataset.get_topics('disease'),
dataset.get_qrels(),
[MAP, nDCG@20]
)
You can find more details about PyTerrier experiments here.
Bibtex:
@inproceedings{Roberts2017TrecPm, title={Overview of the TREC 2017 Precision Medicine Track}, author={Kirk Roberts and Dina Demner-Fushman and Ellen M. Voorhees and William R. Hersh and Steven Bedrick and Alexander J. Lazar and Shubham Pant}, booktitle={TREC}, year={2017} }The TREC Precision Medicine (PM) Track 2018 benchmark. Contains 50 queries containing disease, gene, and target demographic information.
Language: en
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2017/trec-pm-2018")
for query in dataset.queries_iter():
query # namedtuple<query_id, disease, gene, demographic>
You can find more details about the Python API here.
ir_datasets export medline/2017/trec-pm-2018 queries
[query_id] [disease] [gene] [demographic]
...
You can find more details about the CLI here.
import pyterrier as pt
pt.init()
dataset = pt.get_dataset('irds:medline/2017/trec-pm-2018')
index_ref = pt.IndexRef.of('./indices/medline_2017') # assumes you have already built an index
pipeline = pt.BatchRetrieve(index_ref, wmodel='BM25')
# (optionally other pipeline components)
pipeline(dataset.get_topics('disease'))
You can find more details about PyTerrier retrieval here.
Language: en
Note: Uses docs from medline/2017
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2017/trec-pm-2018")
for doc in dataset.docs_iter():
doc # namedtuple<doc_id, title, abstract>
You can find more details about the Python API here.
ir_datasets export medline/2017/trec-pm-2018 docs
[doc_id] [title] [abstract]
...
You can find more details about the CLI here.
import pyterrier as pt
pt.init()
dataset = pt.get_dataset('irds:medline/2017/trec-pm-2018')
# Index medline/2017
indexer = pt.IterDictIndexer('./indices/medline_2017')
index_ref = indexer.index(dataset.get_corpus_iter(), fields=['title', 'abstract'])
You can find more details about PyTerrier indexing here.
Relevance levels
| Rel. | Definition |
|---|---|
| 0 | not relevant |
| 1 | possibly relevant |
| 2 | definitely relevant |
Examples:
import ir_datasets
dataset = ir_datasets.load("medline/2017/trec-pm-2018")
for qrel in dataset.qrels_iter():
qrel # namedtuple<query_id, doc_id, relevance, iteration>
You can find more details about the Python API here.
ir_datasets export medline/2017/trec-pm-2018 qrels --format tsv
[query_id] [doc_id] [relevance] [iteration]
...
You can find more details about the CLI here.
import pyterrier as pt
from pyterrier.measures import *
pt.init()
dataset = pt.get_dataset('irds:medline/2017/trec-pm-2018')
index_ref = pt.IndexRef.of('./indices/medline_2017') # assumes you have already built an index
pipeline = pt.BatchRetrieve(index_ref, wmodel='BM25')
# (optionally other pipeline components)
pt.Experiment(
[pipeline],
dataset.get_topics('disease'),
dataset.get_qrels(),
[MAP, nDCG@20]
)
You can find more details about PyTerrier experiments here.
Bibtex:
@inproceedings{Roberts2018TrecPm, title={Overview of the TREC 2018 Precision Medicine Track}, author={Kirk Roberts and Dina Demner-Fushman and Ellen M. Voorhees and William R. Hersh and Steven Bedrick and Alexander J. Lazar}, booktitle={TREC}, year={2018} }


td Element without max-block-size
Testing Max Block Size
td Element with max-block-size
Testing Max Block Size
DIV Element without max-block-size
Testing Max Block Size
DIV Element with max-block-size
Testing Max Block Size


Drag to rotate 360°
Porsche 911 Turbo
Body Type: Fixed-head Coupe
Engine Type : Turbo-charged petrol
Engine Manufacturer : Porsche
Kerb Weight : 2560 lb
Cylinder : Flat 6
Maximum Torque : 353 Nm
Acceleration (0-60mph) : 5.2 s
Maximum Speed : 155 mph
Gearbox : 4 speed manual
Engine Coolant : Air
RS. 30,800,000
Made with 💙 by ijz-ahd and team


Class: 'mono molecular entity'
http://purl.org/biotop/btl2.owl#MonoMolecularEntity
Annotations (2)
-
definition "A mono-molecular entity is a self connected compound of two atoms or more which exhibit at least one covalent bound. Molecular entities can be isolated molecules or parts of molecules (groups, residue). They may be electrically neutral or not.
In biological systems molecular entities generally occur in very high quantities. In text, references to chemicals are often ambiguous. When we state "water has a molecular weight of 18" we refer to single water molecules. However, saying that "water has a density of 1kg/dm³" under certain conditions then we make a statement about pluralities of water molecules each of which has water molecules as "grains"
Old name: molecular entity
The upper bound of monomolecular entities is shallow. Strictly even a diamond crystal would be a monomolecular entity. One argument against this idea is that a diamond crystal is still a diamond crystal if you take away some portions.
This is not the case with a classical molecule. " ()
-
label "mono molecular entity" ()
Superclasses (1)
Disjoints (2)
Usage (3)


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Join the village and make real connections.
REAL Connections is a community of people who offer friendship, support, and are committed to helping each other when there is a need. It's about sharing time and talent with each other and lending or receiving a helping hand. That might mean getting or giving a ride, finding a trusted handyman, or having someone to call.
Whatever it is, members in our village build new friendships and find peace of mind knowing they have a community to turn to.
Please view our REAL Connections video to hear members speak about the impact REAL Connections has made on their lives.
"People can make a real difference in your life-- especially the people you meet in the REAL Connections Village. Great activities, interesting excxursions, and good friends are all available with just one membership. Try it. You will not regret it!"
John Ammon
Now Serving the Inland, Pomona, and East San Gabriel Valleys of Southern California


Presents a keypad with from 4 to 16 buttons. The keypad can be configured with a bus output or single-bit outputs. When configured for bus outputs, there are two outputs. The bus output (top) is the most recently pressed button value. When configured for single bit outputs, there are 2-4 output bit pins depending on the keypad size. The top pin is the most significant bit. In either case, the bottom output is a single bit clock output and is true when the button is pressed.
When configured as a Phone keypad, the * key outputs a value of 10 (0xa) and the # key outputs a value of 11 (0xb).
The keypad can be configured with a bus output or single-bit outputs. When configured as a bus output, the output is configured as 4 bits for the 16 button, 10 button, and phone configurations, 3 bits for the 8 button configuration, and 2 bits for the 4 button configuration. When configured as a


About
I am an undergraduate CS student at the University of Pittsburgh, expected to graduate May 2019.
I'd ask you not to worry about details like how I use a keyboard; instead, consider what I can offer your company.
Click here to download a PDF version of my resume.


{{/*### Handler=/ TitleBar=Home KyutGrill=homepage2.jpg */}} {{ define "tpl" }} {{ $cf := .ClientFlags }} {{ $ds := band $cf 1 }} {{ $ := . }}
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On November 13, 2015, France’s national football stadium, cafés, and a concert hall were targeted by a series of coordinated attacks. At the Bataclan concert hall, 90 people were killed.
The so-called Islamic State terrorist group claimed responsibility for the attacks.
What has been the long term impact on survivors of the attacks?
Sandrine Martins survived the massacre at the Bataclan theatre and says that beyond the trauma, survivors often feel stigmatised.
She also said resources and sympathy were dwindling.
"It’s like you tell a person that is handicapped, we’re taking away your wheelchair, now you’ll have to walk. He won’t be able to do it. That’s how I feel. I have the impression I’m on that wheelchair and that I’m being told go ahead and walk now," Martins told Euronews.
She explained: "on November 13th we pay homage to the victims, but that’s the only time they think of us. I understand that life must go on but for us, it doesn’t."
One traumatised survivor, Guillaume Valette, committed suicide in 2017. He was recently recognised by French courts as the 131st victim of the attacks, Le Parisien reported.
Commemorations
Today, a series of events are scheduled to remember the victims of the deadliest day witnessed in France’s capital since World War II.
Families of the victims are expected to visit the Bataclan today. There will be speeches by the Justice Minister, the Interior Minister and the Mayor of Paris.
A spokesperson from the Mayor of Paris has said they are deliberately keeping the commemorations low key - at the request of the families.
What is happening to the perpetrators?
Fourteen people face charges over the attacks and 11 are currently held in custody.
The process to prosecute those involved has dragged on.
The investigations only closed in October 2019 and a trial is not expected until at least late 2020.


Our mission is to offer outstanding quality ingredients for our array of customers. Ubatuba is a unique alternative to the ever-so-populating health food spots. Our fast and convenient service get you in and out quick and full stomach of healthier options. Throughout the years, we have perfected the recipes to get the best results when it comes to the featured items on our menu.
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COMPUTER-VISION SNIPPING TOOL
REVERSCREEN is a snipping tool that leverages computer vision algorithms to simplify precise on-screen objects selection and cropping.
The product is licensed under MIT license.
Note: REVERSCREEN executable is not signed with a certificate, so expect Windows to warn you about this app is untrusted.
REVERSCREEN for Windows (setup, 14Mb)The following are experimental builds for 64-bit MacOS and Ubuntu:
Experimental build for macOS Sierra (2Mb) Experimental build for Ubuntu (1Mb)You can also get the source code, and build the app for your platform.


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--- layout: section title: Workshops - NG-DE 2019 - Angular Conference - 2019 in Berlin noindex: true description: > The NG-DE conference is a non-profit conference organised for the community, by the community. We want to create an open, diverse and welcoming conference with fantastic speakers and a warm and friendly environment. ---
All workshops will take place at the hotel of our conference venue on 29. August 2019.
{% for workshop in site.data.workshops %} {% endfor %}


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---
layout: default
---
{{page.model-name}}
{% include nav.html %}
‹ Go back to models
Model parameters
- Task: {{page.description}}
- Imaging modality: {{page.modality}}
- Organ: {{page.organ}}
- Input(s): {{page.input}}
- Output(s): {{page.output}}
- Training set size: {{page.train_no}} / Test set size: {{page.test_no}}
- Performance: {{page.performance}}
- contact: {{page.maintainer}}, email: {{page.email}}
- Size: {{page.size}}
{{ content }}
{% include scripts.html %}


There was no bigger story last summer than the droves of children who crossed the border illegally and without their parents. But as summer faded, so did the stories of the tens of thousands of children who made the long journey from Central America into the United States. Most crossed the border at Texas, and many were transferred to Arizona to be processed by immigration authorities. Our project looks at what happened to these children. Where did they end up? How did their cases play out in court?
These migrant children did not have the right to a court-appointed attorney. Thousands of children whose families couldn’t afford an attorney were left to navigate the complicated civil immigration court proceedings on their own. We look at what happened to those children, hoping to understand the consequences our legal system had on their lives.
You can download Grayscale for free on the preview page at Start Bootstrap.
Visit Download PageCREDITS
Narrator: Claire Bustamante
Photos: Nick Oza
SPECIAL THANKS:
Ken McBride
Nick Oza
Claire Bustamante
Arizona Migrahack
BY:
Kate Gunby
Sociologist
@kategunby
Lucio Villa
News application developer
@luciovilla
Astrid Galván
Journalist
@astridgalvan
Brian White
Journalist
@_BrianWhite
Jeannine Relly
Researcher and assistant professor
University of Arizona School of Journalism
@JeannineRelly
Susan E. Swanberg
Journalist
@seswanberg


<glossProperty>
The <glossProperty>
element is a specialization of the
<data>
element. You can use it to specify additional details about
the preferred term or its subject, for example, the gender of a noun.
Category: Glossentry elements


Our goal is not to create a perfect model that caputes every physical detail but rather invoke some simple mathematics so that we can view the conceptual model through an analytical lense. In the process we will introduce and engage with the mathematical thought that goes into modeling. We will work our way up step by step each time making a single generalization reflecting a bit more physical reality.
in-context


{% extends "base.html" %} {% load cloud_extras %} {% block title %}Private Servers{% endblock %} {% block page_content %}
You have currently no private servers installed.
To install a new private server simply copy and paste the following command into the linux terminal window:
curl http://{{server_addr}}/static/agent.py > ~$USER/agent.py; sudo sh -c "while true; do python ~$USER/agent.py; sleep 3; done"And that's that.
Server #{{forloop.counter}}
Agent v{{server|dict_get:"agent_version"}}
ID {{server|dict_get:"_id"}}
UUID {{server|dict_get:"uuid"}}
Uptime {{server|dict_get:"uptime"}}
IP address {{server|dict_get:"ip"}}
Public IP address {{server|dict_get:"ip_remote"}}
Load Average {{server|dict_get:"loadavg"}}
Current CPU Usage {{server|dict_get:"cpu_usage"}}
Current Memory Usage {{server|dict_get:"memory_usage"}}
Current Physical Disks {{server|dict_get:"physical_disks"}}
Current Disks Usage {{server|dict_get:"disks_usage"}}
CPU Virtualization {{server|dict_get:"cpu_virtualization"}}
CPU Info {{server|dict_get:"cpu_info"}}
Last Seen {{server|dict_get:"last_seen"}}
Activities:
{% for activity in server|dict_get:"uuid"|get_server_activities %}
{% if forloop.counter < 5 %}
{{activity}}
{% endif %}
{% endfor %}


Empresas
this tile flips horizontally and swaps between images randomly
this tile flips horizontally and swaps between images randomly front title
Impuestos
CFDI


eMaTe
eMaTe it is a python package which the main goal is to provide methods capable of estimating the spectral densities and trace functions of large sparse matrices. eMaTe can run in both CPU and GPU and can estimate the spectral density and related trace functions, such as entropy and Estrada index, even in directed or undirected networks with million of nodes.
Install
pip install emate
If you a have a GPU you should also install cupy.
Kernel Polynomial Method (KPM)
The Kernel Polynomial Method can estimate the spectral density of large sparse Hermitan matrices with a computational cost almost linear. This method combines three key ingredients: the Chebyshev expansion + the stochastic trace estimator + kernel smoothing.
Example
import networkx as nx
import numpy as np
n = 3000
g = nx.erdos_renyi_graph(n , 3/n)
W = nx.adjacency_matrix(g)
vals = np.linalg.eigvals(W.todense()).real
from emate.hermitian import tfkpm
num_moments = 40
num_vecs = 40
extra_points = 10
ek, rho = tfkpm(W, num_moments, num_vecs, extra_points)
import matplotlib.pyplot as plt
plt.hist(vals, density=True, bins=100, alpha=.9, color="steelblue")
plt.scatter(ek, rho, c="tomato", zorder=999, alpha=0.9, marker="d")
If the CUPY package it is available in your machine, you can also use the cupy implementation. When compared to tf-kpm, the Cupy-kpm is slower for median matrices (100k) and faster for larger matrices (> 10^6). The main reason it’s because the tf-kpm was implemented in order to calc all te moments in a single step.
import matplotlib.pyplot as plt
from emate.hermitian import cupykpm
num_moments = 40
num_vecs = 40
extra_points = 10
ek, rho = cupykpm(W.tocsr(), num_moments, num_vecs, extra_points)
plt.hist(vals, density=True, bins=100, alpha=.9, color="steelblue")
plt.scatter(ek.get(), rho.get(), c="tomato", zorder=999, alpha=0.9, marker="d")
Stochastic Lanczos Quadrature (SLQ)
The problem of estimating the trace of matrix functions appears in applications ranging from machine learning and scientific computing, to computational biology.[2]
Example
Computing the Estrada index
from emate.symmetric.slq import pyslq
import tensorflow as tf
def trace_function(eig_vals):
return tf.exp(eig_vals)
num_vecs = 100
num_steps = 50
approximated_estrada_index, _ = pyslq(L_sparse, num_vecs, num_steps, trace_function)
exact_estrada_index = np.sum(np.exp(vals_laplacian))
approximated_estrada_index, exact_estrada_index
The above code returns
(3058.012, 3063.16457163222)
Entropy
import scipy
import scipy.sparse
def entropy(eig_vals):
s = 0.
for val in eig_vals:
if val > 0:
s += -val*np.log(val)
return s
L = np.array(G.laplacian(normalized=True), dtype=np.float64)
vals_laplacian = np.linalg.eigvalsh(L).real
exact_entropy = entropy(vals_laplacian)
def trace_function(eig_vals):
def entropy(val):
return tf.cond(val>0, lambda:-val*tf.log(val), lambda: 0.)
return tf.map_fn(entropy, eig_vals)
L_sparse = scipy.sparse.coo_matrix(L)
num_vecs = 100
num_steps = 50
approximated_entropy, _ = pyslq(L_sparse, num_vecs, num_steps, trace_function)
approximated_entropy, exact_entropy
(-509.46283, -512.5283224633046)
[3] The Kernel Polynomial Method applied to tight binding systems with time-dependence


As one of three brothers who have an interest in technology, I earned a Bachelor of Science in Computer Science and a Masters of Science in IT Management while serving as a Pilot in the U.S. Army. I am a current Certified Information System Security Professional (CISSP), Certified Ethical Hacker (CEH), a Cisco Certified Network Associate (CCNA), and Linux+ certified. I've been trying to relearn web development, the newer frameworks, and multiple languages for full stack web development. Although I am currently working as a network analyst, I have found that I prefer the developer role and I'm preparing myself for some freelance work.


How has the distribution of genders for anchors and presenters evolved over the course
of the years? Was there a gender bias? If yes, how has it changed?
There are over 100 different presenter roles in the RTS dataset. Here we have selected to plot what we thought are the
most interesting ones.
In general we can see various patterns. For 'Interviewer' and 'Presenter,' we see a very nice progress over the last decades.
For such roles as 'Producer, ' there is not much progress and these roles stay a pretty much dominated by men.
There are also roles where the gender balance was essentially fair since earlier years. For example, this is the case
for 'weather presenter' role.
In general we can observe that the roles that have a direct contact with the audience (in audio or visual format) have
made very good progress in term of equal gender representation over the past years and are now pretty close to equality
(with repect to the number of male and female). This, for example, can be seen for 'weather presenter', 'Interviewer'
and 'Presenter' roles.
On the other hand, some roles have not made any progress. One notable case in the 'Interviewed' case. This is the list of all
people (usually experts) that have been interviewed, on very various topics, by RTS. It gives a nice image of the society
(mostly at the elite level). We can see that there is still a lot of progress to be made in this front.


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UD for Swedish Sign Language
Tokenization and Word Segmentation
- The Swedish Sign Language Corpus (SSLC) treebank depends on the sign glosses provided in the SSLC source material, so the source text is already tokenized.
- Sign glosses are always delimited by whitespace.
- There is no punctuation.
- Multiword tokens are not used.
Morphology
Tags
- Swedish Sign Language uses 12 of the universal tags.
- The following tags are not used:
- SYM and PUNCT are not used because this is not a written-language corpus.
- PART is not used because we do not see signs that are special enough to warrant this.
- PROPN is not used because there is no syntactic/morphological distinction with other nouns, and the corresponding semantic information is present in the glosses (proper nouns contain the
@en
substring). - SCONJ is not used because subordination is often only marked with non-manual markers that are not present in the transcription, or in a few cases with adverbs.
- The auxiliary tag (AUX) is used for the following cases, with remaining verb-like signs being tagged as VERB:
- The copula VARA (be) and the copula-like verbs HETA (be named) and SE-UT (look like).
- The signs PERF and PERF-NEG that mark perfect tense.
- Modal verbs such as SKA, VILL, KAN that are used with a main verb.
- The tag DET is used for:
- The sign EN (one) when modifying a noun as an article.
- Pointing signs used with a noun.
- The tag PRON is used for:
- Pronoun signs such as PRO1, NÅGON (somebody), etc.
- Pointing signs when used as heads of noun phrases.
Features
- No UD morphological features are used for Swedish Sign Language.
- Note that linearizing and transcribing or glossing a signed language is not trivial, and results in some degree of information loss. If data in Swedish Sign Language, or some other sign language, using a different convention than the Swedish Sign Language Corpus (glossing of manual signs) is to be included in UD, this may be different.
- Negated verbs have glosses that end with
-INTE
(lexically negative; suppletive) or*INTE
(cliticized manual negation marking). - Lemmas are not used.
Syntax
- Subjects may occur on either side of the verb, and often subjects are repeated and may occur on both sides of the verb. In this case, the conj relation holds between the second and the first sign, and the first sign has an nsubj relation to the verb.
- Objects generally follow the verb, without preposition.
- Copula constructions in nonverbal clauses are used for …
- The following subtypes are used in Swedish Sign Language:
- acl:relcl for relative clauses
- compound:prt for verb particles
- compound:svc for serial verb constructions
- nmod:poss for possessive/genitive modifiers
Treebanks
There is one Swedish Sign Language UD treebank:


| Date | Name | Description | Duration |
|---|---|---|---|
| 19/07/2002 18:21:30 | added email support option | added a menu item to email support which calls the default email program with a subject and body related to the registered status of the app. if registered then it includes the users name and key  |
1  |
| 0.5 | word spelling checker | I have knocked up some quick code to integrate with MS Word's spelling checker cntrl+F7 in the description or text weighting edits.  |
0.5  |
| 19/07/2002 14:47:58 | added more FILE options | added options to Explore @ - open explorer at the file path Print File - launch the defined app in print mode  |
1  |
| 19/07/2002 13:17:28 | changed looknfeel of graphical properties dialog | changed looknfeel of graphical properties dialog it now looks a little more like a properties tab (I think :])  |
1  |
| 19/07/2002 12:06:51 | relative paths | added the ability to turn file references from absolute paths to relative paths (relative to the model) accessed by double clicking on the item in the list and choosing Make Path Reference  |
1  |
| ID | Name | Raised Date | Closed Date | Description | Resolution |
|---|---|---|---|---|---|
| 344 | system crashes when changing node colours | 18/07/2002 20:21:33 | 18/07/2002 13:10:33 | an access violation occurs when closing the graphical node properties dialog (sometimes).   |
I have removed the form ex attribute code and it seems stable now, this means that the form is outside the main mdi form and is not always on top. This is not as user friendly but it doesn't crash the system so is much more user friendly. This will be like this until I implement a proper properties list on the graph edit form itself.  |
| ID | Name | Raised Date | Status | Criticality | Description |
|---|---|---|---|---|---|
| 62 | icons on buttons are not transparent | 17/04/2002 | OPEN | LOW | need to turn the .ico into .bmp and setup the mask property  |
| 321 | transmute a branch to entity does not update treebrowser | 03/07/2002 15:00:07 | OPEN | LOW | the tree is not updated and neither is the list if the list is displayed  |
| 208 | entity create needs saved twice | 30/05/2002 16:24:02 | OPEN | MEDIUM | when creating an entity, and saving it. the save is made but the form brings up the save button once again. the second save commits and does not ask for another save this is a sporadic problem and may be due to an oversensitive keyboard setting on the laptop?  |
| 134 | the hierarchy browser hierarchy should maintain expansion | 25/04/2002 17:55:54 | OPEN | LOW | during restructuring, the hierarchy should leave expanded the items which are expanded  |
| 133 | The hierarchy browser tree refreshes too much on drag | 25/04/2002 17:54:37 | OPEN | LOW | this can be disconcerting when dragging, perhaps the timer is not long enough?  |
| ID | Name | Raised Date | Status | Raised By | Description |
|---|


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Excellent article – Tabs are becoming a real good way especially for tablets to show content.
Thanks Pullo!
Excellent article – Tabs are becoming a real good way especially for tablets to show content.
Thanks Pullo!


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Users with read access can get the SHA-1 of a commit reference:
GET /repos/:owner/:repo/commits/:ref
To access the API you must provide a custom media type in the Accept
header:
application/vnd.github.VERSION.sha
To check if a remote reference's SHA-1 is the same as your local reference's SHA-1, make a GET
request and provide the current SHA-1 for the local reference as the ETag.
The SHA-1 of the commit reference.
Status: 200 OK
814412cfbd631109df337e16c807207e78c0d24e


- Add symfony-meta folder as PHP library into plugin (Thomas Schulz) #1286
- Routes: Adding support for inlined wildcard requirements #1273 (Daniel Espendiller)
- Symfony 4.3: Support "Always Include Route Default Values" parameter syntax #1271 (Daniel Espendiller)


Remember that each sentence is classified by the combination of dependent and independent clauses it contains.
Further hints will show you which types of clauses make up the above sentence.
Is the sentence below considered a simple, compound, complex, or compound-complex sentence?
person(1) clauses[randRange(0,13)].
(function() { var clauses = ' Simple'; return clauses; })()
"clause1" is an independent clause.
This is a simple sentence.
person(1) clauses[randRange(0,4)], conj[randRange(0,3)] person(2) clauses[randRange(5,13)].
" Compound"
"clause1" is an independent clause.
"clause2" is an independent clause.
This is a compound sentence.
deps[randRange(0,3)] person(1) clauses[randRange(9,13)], person(2) clauses[randRange(0,8)].
" Complex"
"clause1" is a dependent clause.
"clause2" is an independent clause.
This is a complex sentence.
deps[randRange(0,3)] person(1) clauses[randRange(8,13)], person(2) clauses[randRange(4,7)], conj[randRange(0,3)] person(3) clauses[randRange(0,3)].
" Compound-complex"
"clause1" is a dependent clause.
"clause2" is an independent clause.
"clause3" is an independent clause.
This is a compound-complex sentence.


References
References:#
-
Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge, MA (1998)
-
Watkins, C.: Learning from Delayed Rewards. Ph.D. thesis, University of Cambridge, Cambridge, England (1989)
-
Thrun, S.B.: an Efficient Exploration in Reinforcement Learning. Technical Report CMU-CS-92-102, Carnegie Mellon University, Pittsburgh, PA, USA (1992)
-
Brafman, R.I., Tennenholtz, M.: R-MAX - a general polynomial time algorithm for near-optimal Reinforcement learning. Journal of Machine Learning Research 3 (2002) 213–231
-
Ishii, S., Yoshida, W., Yoshimoto, J.: Control of exploitation-exploration meta parameter in Reinforcement learning. Neural Networks 15(4-6) (2002) 665–687
-
Heidrich-Meisner, V.: Interview with Richard S. Sutton. K¨unstliche Intelligenz 3 (2009) 41–43
-
Vermorel, J., Mohri, M.: Multi-armed bandit algorithms and empirical evaluation. In: Proceedings of the 16th European Conference on Machine Learning (ECML’05), Porto, Portugal (2005) 437–448
-
Caelen, O., Bontempi, G.: Improving the exploration strategy in bandit algorithms. In: Learning and Intelligent Optimization. Number 5313 in LNCS. Springer (2008) 56–68
-
Rummery, G.A., Niranjan, M.: On-line Q-learning using connectionist systems. Technical Report CUED/F- INFENG/TR 166, Cambridge University (1994)
-
Bertsekas, D.P.: Dynamic Programming: Deterministic and Stochastic Models. Prentice Hall (1987)
-
George, A.P., Powell, W.B.: Adaptive step sizes for recursive estimation with applications in approximate dynamic programming. Machine Learning 65(1) (2006) 167–198
-
Robbins, H.: Some aspects of the sequential design of experiments. Bulletin of the American Mathematical Society 58 (1952) 527–535
-
Awerbuch, B., Kleinberg, R.D.: Adaptive routing with end-to-end feedback: Distributed learning and geometric approaches. In: Proceedings of the 36th Annual ACM Symposium on Theory of Computing, Chicago, IL, USA, ACM (2004) 45–53
-
Azoulay-Schwartz, R., Kraus, S., Wilkenfeld, J.: Exploitation vs. exploration: Choosing a supplier in an environment of incomplete information. Decision Support Systems 38(1) (2004) 1–18
-
Mnih, Volodymyr, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, et al. ‘Human-Level Control through Deep Reinforcement Learning’. Nature 518, no. 7540 (25 February 2015): 529–33. doi:10.1038/nature14236
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Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., Riedmiller, M., 2013. Playing Atari with Deep Reinforcement Learning. arXiv preprint arXiv:1312.5602.


public interface Event extends Extendable
| Modifier and Type | Interface and Description |
|---|---|
static class |
Event.Type
Event types built into the library.
|
| Modifier and Type | Method and Description |
|---|---|
Event |
copy() |
void |
delegate()
dispatch the event to all children of the handler.
|
void |
dispatch(Handler handler) |
Connection |
getConnection() |
java.lang.Object |
getContext() |
Delivery |
getDelivery() |
EventType |
getEventType() |
Link |
getLink() |
Reactor |
getReactor() |
Receiver |
getReceiver() |
Handler |
getRootHandler()
The
Handler at the root of the handler tree. |
Selectable |
getSelectable() |
Sender |
getSender() |
Session |
getSession() |
Task |
getTask() |
Transport |
getTransport() |
Event.Type |
getType()
A concrete event type of core events.
|
void |
redispatch(EventType as_type,
Handler handler)
Synchronously redispatch the current event as a new
EventType on the provided handler and it's children. |
attachments
EventType getEventType()
Event.Type getType()
Event.Type.NON_CORE_EVENT
will be returnedjava.lang.Object getContext()
Handler getRootHandler()
redispatch(EventType, Handler)
void dispatch(Handler handler) throws HandlerException
HandlerException
void redispatch(EventType as_type, Handler handler) throws HandlerException
EventType
on the provided handler and it's children.
Note: the redispatch()
will complete before children of the current handler have had the current event dispatched, see delegate()
.
as_type
- Type of event to dispatchhandler
- The handler where to start the dispatch. Use getRootHandler()
to redispatch the new event to all handlers in the tree.HandlerException
- A wrapper exception of any unhandled exception thrown by handler
void delegate() throws HandlerException
dispatch(Handler)
HandlerException
Connection getConnection()
Session getSession()
Link getLink()
Sender getSender()
Receiver getReceiver()
Delivery getDelivery()
Transport getTransport()
Reactor getReactor()
Selectable getSelectable()
Task getTask()
Event copy()


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