Grants for Climate Change Research
EPA’s Science to Achieve Results or STAR program funds research grants and graduate fellowships in numerous environmental science and engineering disciplines through a competitive solicitation process and independent peer review. In addition, through this same competitive process, EPA periodically establishes large research centers in specific areas of national environmental concern. The program engages the nation’s best scientists and engineers in targeted research that complements EPA’s own intramural research program and partners in other federal agencies.
EPA’s STAR program supports research focusing on a few important aspects of how climate change affects air pollution:
- Investigating the impact of climate change on air pollution gases and particles
- Understanding the underlying factors contributing to air pollution formation and transport
- Using modeling tools to better understand the impacts of extreme events on air quality as well as provide better predictions of future air quality under a changed climate.
The following grants have been awarded to academic institutions and non-profit research organizations to conduct research to better understand the climate change impact on air quality, water quality and human health.
- Indoor Air and Climate Change
- Air quality and climate impacts of cooking, heating and lighting practices
EPA awarded six grants totaling almost $9 million in 2014 to support research on the impacts on air quality and climate from residential cooking, heating, or lighting. The research is quantifying the improvements in climate and ambient and indoor air quality, and the subsequent impacts on health and welfare, resulting from ongoing, planned, or potential interventions in cooking, heating, or lighting practices. - Impacts of extreme events on air and water quality under a changing climate
EPA awarded 14 grants totaling almost $9 million in 2012 to develop and demonstrate innovative tools and technologies for providing information and capacity to adequately prepare for climate-induced changes in extreme events. A major goal of these projects is to gain a better understanding of extreme events and to establish ways for climate scientists, impact assessment modelers, air and water quality managers, and other stakeholders to co-produce information necessary to form sound policy in relation to extreme events and their impact on air and water quality under a changing climate. - Black carbon’s role in climate change and air quality
EPA awarded 10 grants totaling over $7.5 million in 2011 and 2012 for projects on black carbon, which contributes to human health impacts, visibility degradation and climate change. These grants focus on various aspects of the black carbon issue, such as better accounting for its emissions, tracking its climate-relevant properties as it ages in the atmosphere, and better representing its ability to impact formation of cloud droplets. The research on this short-lived climate forcer helps us to better understand its effects on climate change and air quality.


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Speech
The Education Secretary speaks about the department's new policies aimed at recruiting and training the next generation of teachers.
Thank you Steve for that introduction and thank you for all the great work you and the College have done over the past year.
Can I also take this opportunity to thank Steve’s tireless deputy Toby Salt - who is about to take up a new challenge as Chief Executive of the Ormiston Academy chain - and Andy Buck, who has done a brilliant job in establishing Teaching Schools - who is going to work for ULT?
It turns out that a downside of devolving power from the centre is that is creates great career opportunities for some of our best people.
But I think that’s a price worth paying…..
Those of you who have heard me speak before are probably expecting a brief tour around the educational policies of those countries that dominate the OECD’s PISA league table.
And it’s true we have looked all over the world in developing our policies.
Our curriculum reforms were inspired by the high expectations for all children in Singapore and Hong Kong.
The success of Finland and South Korea has informed our focus on getting more of our very best graduates into teaching.
The example of charter schools in New Orleans and New York - which have transformed the life chances of poorer children in those cities - have been critical in developing free school policy.
But while I’ve been inspired by Singapore, Finland and New Orleans another success story has perhaps had an even greater influence on my thinking. And it’s one that’s closer to home. London.
Until 2004 London always underperformed the rest of the country in exams. In the seventies and eighties inner London schools were seen by many as a by-word for failure. While some were, in fact, doing well in difficult circumstances there were serious problems. Poor behaviour was endemic, aspiration was low, life chances were stunted.
But over the last few decades there has been a transformation.
The difference between London and the rest of the country may not seem that great at first glance. 62 per cent of children achieve five good GCSEs with English and Maths compared with 58 per cent nationally.
Dig a little deeper, though, and there are some startling results. Across the country just 35 per cent of children on free school meals achieve five good GCSEs with English and Maths - a scandalously low figure - but in inner-London 52 per cent meet it - just a few points off the average for all children.
And this gap between the achievement of children in the capital and elsewhere exists for all ethnic groups and all income bands. For instance almost half of London’s poorest white pupils get five good GCSEs with English and Maths compared with 37 per cent nationally.
Nor has the success been patchy - there have been big improvements across the capital. There is now just one London secondary school below the floor standard.
So how has this happened?
Of course London has many advantages - it is a dynamic city with a fantastic cultural heritage. It benefits from a diverse mix of, often highly aspirational, communities. As the centre of so many professions - politics, media, the law - it is much easier to identify role models for young people than in other parts of the country.
But those things have been true for many years and London’s success is a more recent phenomenon. What’s really made the difference is that London has been the laboratory for educational reform over the past decade.
The last Government launched the London Challenge in 2003. There were several elements to this but the three most important were:
Each of these strands has had a profound effect on performance and on my thinking. In each case this Government has learnt the lessons and is spreading the benefits of these reforms across the rest of the country.
The sponsored academy revolution began in London. Until 2010 there were more in London than the rest of the country put together - and there are still more than in any other region.
Nearly all of them have seen massive improvements from their predecessor school - given a new lease of life by a committed sponsor and the independence to innovate.
There are a small number of schools where children on free school meals both represent more than a third of all pupils and achieve above the national average. These are the jewels in the crown of the state education system - a standing rebuke to everyone who claims poorer children are destined to do worse than others. And when you look for them across London you start to see a pattern.
In Hackney there is one such school. It won’t surprise anyone to learn that it’s Mossbourne Academy.
In Southwark there are two - ARK Walworth Academy and Harris Bermondsey Academy.
In Westminster there are three - Pimlico Academy, Paddington ULT Academy and one non-academy: St. Marylebone Church of England School.
In each of these local authorities the incredible performance of new sponsored academies has acted as a spur to others. In Southwark the percentage of free school meal children achieving five good GCSE with English and Maths has increased by 23 percentage points in 4 years; in Westminster 18 percentage points; in Hackney by 15.
Since the election this Government - inspired by these successes - has turbo-charged the sponsored academy programme. By this September we will have increased the number we inherited by well over 100 per cent. And, crucially, we have expanded the programme into primary schools - more than 200 have now been brokered and 34 are already open.
I know this has been one of our more controversial reforms - some of the usual suspects have sought to protect underperforming schools from necessary change. But it seems deeply irresponsible to me to allow schools to fail year after year when organisations, like Harris, that have proven their ability to turn round schools time and time again are willing to help.
Academies, though, are only part of what made the London Challenge successful. The leadership strand of the programme focused on identifying “system leaders” to support weaker schools. This proved extremely successful. Schools in Tower Hamlets and Newham - like Swanlea and Rokeby - have been amongst the fastest improvers in recent years - and have done so by working closely with each other to drive up standards.
The legacy of this success is widespread support for system leadership as the best method of school improvement. As former chief inspector Christine Gilbert put it in a recent speech: “we’ve reached a tipping point in favour of schools, school leaders, and teachers themselves, as the primary drivers of systemic improvement”.
That is reflected both in the National Leader of Education programme - which is being massively expanded by this Government - as well as the great work being done by good and outstanding schools that have converted to academy status to help others.
Indeed one of the Tower Hamlets’ schools originally identified as requiring support under the London Challenge - Bethnal Green Technology College - converted to academy status as an outstanding school in January this year and is, as a condition of that status, supporting Dartford Technology College, a school currently in special measures.
Increasingly the very best schools are going beyond ad hoc support for weaker schools and establishing their own chains and federations - in the same way Harris, Haberdashers and John Cabot City Technology Colleges did in the early years of the academy programme. 85 outstanding schools are now signed up as academy sponsors.
The third key strand of the London Challenge was a focus on increasing the number of outstanding teachers through professional development and recruitment of the best graduates via Teach First - which was in its first few years a predominantly London centred programme.
Of the 1,000 Teach First trainees who completed training under the last Government over three-quarters were based in a London school.
While these 750 plus teachers represent a small percentage of the London workforce they have had a disproportionate impact. It is notable that the schools I mentioned earlier that help children on free school meals outperform the average have all relied heavily on Teach First in their recruitment.
Indeed many Teach Firsters have already reached leadership positions in these schools and others like them. They are often young people who would not have considered teaching without the additional prestige of Teach First, or the opportunity to start working in a challenging school straight away, but who have now decided to commit their lives to helping some of the most disadvantaged children in our society match - or supersede - their own achievements.
Their success emphasises one of the key messages of international research over the past few years: no education system can outperform its teachers and the most successful jurisdictions, though they may differ hugely in other aspects, share a focus on recruiting the very best graduates and training them in outstanding institutions.
Under this Government Teach First have been given the funding to grow in commensurate proportion to their ambitions. By the end of this Parliament they plan to train 1,500 graduates a year; three times as many as they were doing at the beginning. They have developed a bespoke primary programme and expanded to all parts of the country.
But we are not just growing Teach First itself we are also applying the key lessons of that programme to the whole teacher training system. And how we’re doing that is what I want to focus on today.
Some changes we’ve already made.
One lesson from Teach First, as well as of PISA, is the importance of attracting the best graduates.
So we have introduced bursaries of up to £20,000 to attract the very best science and maths graduates. And we have raised the bar for potential trainees - they now need at least a second class degree to receive a bursary - to signal to undergraduates the intellectual rigour required to become a teacher.
We know that a big reason for Teach First’s success in recruiting hundreds of graduates from our best universities is the sense of prestige attached to a programme badged as elite. We now need to extend that sense of prestige to teaching as a whole.
As a result of these changes we have already seen a 12 per cent increase in the proportion of candidates with a 2:1 or first class degree accepted on to maths, physics, chemistry and modern foreign languages teacher training courses.
In physics - traditionally the hardest subject to recruit for - there has been an incredible 29 per cent rise in the proportion of graduates with a good degree accepted on to courses.
And attitudes are changing too.
In their annual survey of final year undergraduates the Teaching Agency found that:
81 per cent agreed that teaching had real status and kudos - up 4 per cent since 2010.
72 per cent thought their friends and family would react positively to them becoming a teacher - up 6 per cent since 2010.
And, encouragingly, 71 per cent thought the image of teaching is improving.
But it’s not just about ensuring that we recruit the very best talent available. We also need to make sure that our very best educators are at the heart of training each new generation of teachers.
And the best vehicle for doing this is something else that started in London as part of the Challenge - the Teaching School - pioneered by George Berwick the visionary headteacher of Ravens Wood School.
There were just a handful of Teaching Schools in 2010 but the potential was obvious. The idea is a simple one: take the very best schools, ones that are already working to improve other schools, and put them in charge of teacher training and professional development for the whole system.
Via the great work of the National College this Government has already set up a network of 200 Teaching Schools - with the aim of opening 500 by the end of the Parliament. Their impact has been immediate and profound.
Fantastic projects have popped up all over the country - not driven by the demands of Government or by Ministers’ prejudices but by school leaders.
Whether it’s Fairlawn Primary in Lewisham supporting Maths teaching across the borough.
Or Wroxham school in Hertfordshire working with Cambridge University to develop a new pedagogy that breaks free of previous obsessions with ability-labels.
Or the network of Teaching Schools across the North-West who are developing their own school improvement programme for local schools.
And, of course, nearly all Teaching Schools are getting much more involved in teacher training.
Pushing more teacher training through schools has been an aim of successive Governments since the late eighties. And there have been important initiatives. The last Conservative Government allowed groups of schools to form together to offer teacher training. The Labour Government introduced the Graduate Teacher Programme - allowing typically older trainees to learn on the job - as well as Teach First.
In fact this is a global shift. As the OECD’s head of education Andreas Schleicher put it in a speech last year “many countries have shifted the emphasis from academic preparation to preparing professionals in schools instead. Teachers now get into classrooms earlier, spend more time on-site in schools, and get more and better support in the process”.
But previous efforts in this country have always been piecemeal - hamstrung by the lack of a proper network of outstanding schools to deliver training on a serious scale.
Now we have the Teaching School network.
Earlier this year we launched a pilot version of a new programme called School Direct. Teaching Schools were offered the opportunity to bid for teacher training places.
Those participating will be able to recruit their own trainees and develop their own training programme in partnership with a university. In return for this additional control the schools will be expected to find a job for the trainee once they finish their training. As such it represents a better deal for both schools and trainees.
Because of the short notice and the select group of schools involved we expected a maximum of 500 places would be bid for - instead it was over 1,000, of which 914 were allocated. We were blown away by schools’ enthusiasm.
Now these places have been allocated, the schools involved are already recruiting trainees; and working with a wide-range of universities to develop high-quality training programmes; and putting teacher training at the heart of their plans for the future.
For example Harris academies have decided to partner with Canterbury Christ Church university and have worked closely with them to select trainees and design a training programme. Harris staff will be as closely involved as possible in the core teaching days on the programme, and will increase this involvement as the programme evolves. Staff from Harris have already accompanied staff from Canterbury Christ Church on a research trip to Finland.
And Cabot academies have developed a programme that will see each trainee mentored by an existing outstanding teacher in their chain - following a bespoke 10 day induction in their schools before Autumn term begins.
As we grow the Teaching School network, many more heads have come to us, asking to be involved.
So we are going to expand School Direct significantly over the next few years.
Schools won’t have to be part of a Teaching School alliance to get involved but we envisage that most will - because of the advantages of training across a group of schools.
And while we anticipate that the majority of schools participating will want a strong partnership with a higher education institution, we expect that some of the very best schools will want to become their own provider.
Indeed some of the most forward thinking Teaching Schools and academy chains have already gone down this route.
Like the Kemnal academies trust who will use the wealth of experience in teacher training across their member schools to offer courses in English, mathematics, physics, chemistry and MFL from September.
Or Tudor Grange Teaching School alliance who will offer courses in the same subjects from September 2012 with Masters level credits awarded by Cumbria University.
By the end of the Parliament we expect as many as 10,000 students a year could be trained by schools that are either offering Schools Direct places or are full providers of teacher training.
So there will be a spectrum of engagement for those schools that want to get involved. Some schools may not want to get involved at all. Many will want to participate in School Direct - having the opportunity to recruit staff and develop training programmes with the support and assistance of existing providers. Others will want to run the whole show - taking control of the process from start to finish.
As these programmes grow, more and more schools will be able to recruit, train and hire their own teachers; working in partnership with other schools and top-quality ITT providers to give new teachers the best possible start to their careers.
New recruits will learn and train in schools, working with experienced teachers and putting their lessons into practice from day one.
And they will be recruited with the expectation that they will be employed at the school at the end of their training - something which the traditional, university-based PGCE could never offer.
Of course, for existing providers involved in teacher training this will mean some big changes.
We want to ensure the very best providers remain committed to teacher education so universities, and others, rated “outstanding” by Ofsted will be guaranteed their existing level of places for the next two years.
But we will no longer guarantee places to institutions rated good or lower. They will compete for training places through School Direct, designing courses in collaboration with schools. If schools don’t rate their provision, they will go out of business.
And we’re going to work quickly in identifying and shutting down providers which simply aren’t good enough. If they receive two “Requires Improvement” judgements under the new - tougher - Ofsted framework - they will be swiftly de-accredited.
If an ITT provider isn’t delivering the sort of high-quality, highly-respected training which each new teacher deserves and needs - then they have no place delivering training at all.
Along with recruiting the best university-leavers and ensuring they are trained in the best schools and universities, I also want to do more to attract more of the best and brightest career-changers.
The Graduate Teacher Programme, or GTP, has been in place since 1998. In that time it has delivered some superb training, and recruited some brilliant teachers.
But it has also suffered from some serious flaws. Recruitment has been ad hoc - there has never been a sense that the programme is targeted at high-fliers.
There has never been a central website that any career-changer interested in becoming a teacher could go to to find places.
And sometimes schools have felt frustrated by restrictions over salary and training.
So we are going to close the GTP, but build on its strengths to launch a new, school-led teacher training programme for the best career-changers.
From September 2013, a new employment-based strand of School Direct will be available for candidates who have already gained at least three years valuable experience in other careers.
Any school that wants to participate will be asked to advertise places on a single website which will allow the Teaching Agency to better market the programme to the target audience.
Schools will have much greater control of funding - they will be able to decide how much to spend on trainees’ salaries and how much on training - giving them the autonomy and flexibility to decide how to get the biggest possible bang for their buck.
And to help schools in deprived areas to recruit and train the very best teachers, schools with 35 per cent or more of their pupils on free school meals will receive a 10 per cent funding premium.
In 2013-14, we will fund up to 5,000 places on employment-based School Direct- more than the number of places on the GTP this year.
The cumulative impact of these changes on initial teacher training will be revolutionary. By the end of this parliament well over half of all training places will be delivered by schools whether through direct provision; Teach First; School Direct; or our new employment-based route.
Most of the rest will be doing PGCE courses in existing providers rated outstanding.
The weakest providers will no longer be in business. They will have been de-accredited following Ofsted inspections or unable to persuade schools to commission support from them.
This represents a huge opportunity for school leaders - to take control of teacher training - to create programmes that reflect their school’s ethos - to recruit better trainees.
I was delighted to read in the National College’s independent survey of 2,250 school leaders that 98 per cent think it’s a great job. It is a great job and one that makes such a difference. I want to thank you for all that you have done so far as leaders to improve the life chances of the children and young people in your care. I know that your roles are challenging and that this government is asking even more of you but that is because I believe the children and young people in this country deserve the very best.
I am asking you to work with me to move these important proposals forward. It is a big responsibility - you will need to show that you can manage the development and improvement of the profession rather than looking to others to do it for you. But if London’s improvement has taught us anything it is that putting schools in control of their own destiny is the key to success.
ENDS
Published: 14 June 2012


On a usual basis, I rarely share my psychedelic experiences with anybody but my closest acquaintances. It's in this case I will break this rule, because it is in my best interest to further the already expanding usage of this plant.
Whether or not it actually places the user into a seperate dimension, I have no clue. But I do know that it is like no substance I have yet to experience and thus I am forced to analyze the situation on a frequent basis. As my friend Weazel, once spoke about the effects of Salvia divinorum, I will repeat his quote: 'It definitely puts you in a situation.'
It was warm, summer day when I received the package that I had ordered exactly a week from the date it was dropped off at my door step. Excited, I tore open the rather large package to find (to my own initial disgrace) 2 small bags that contained a gram of Salvia 5x each. Of course, little did I know.
Weazel, not exactly the most enthusiastic about the substance itself, gave me a pathetic look when I asked him to visit me in a smoking session. Though, being the friend he is, opted to follow me out to his blazer where we would soon find out just what the hell we were getting into.
With a homemade pipe, I dumped what could have possibly been the equivalent to a fourth of the bag into the bowl. I don't really know how much it was but I do know that we were able to carry out 3 more equally effective sessions afterwards, so therefore I will make the estimate that it was around a fourth of a bag.
Within a 1 1/2 minutes, we had consumed the entire bowl. The initial buzz was much like the stereotypical Salvia buzz: Silenced and disoriented.
I looked to Weazel and asked him what the hell was happening. He looked at me with the same question written on his face and shrugged his shoulders. Blackout...
Weazel was no longer occupying my reality, though I venture to say that I had was no longer occupying my own reality. I was now in a world where I was strapped to the boundries of a new dimension, struggling to get free.  I wanted to explore and I was not allowed to do so. Understandably, I was still mistaken that exploration would require physical movement. Since Salvia usually puts me into a paralyzed state, it took me another trip to understand exploration would require metaphysical transportation through the vehicle of my mind.
Nonetheless, I struggled with the drug, wanting to explore this new realm. I gathered enough strength turn my head towards Weazel, who had began integrating himself into my reality, but only to the point where I could see his eyeballs, nostrils and mouth. He was the epitomy of the cheshire cat, a chameleon within a blitzkrieg of fluid colors.
Speaking was an impossibility...but the voices that surrounded me giggled, shouting demands that I relax.  This was my world and what the hell were they doing in it. A rather rude attitude towards them (the inhabitant voices), considering it was anything but my world and who was I to come knocking on their door and tell them how I was going to behave in their household. Being an Eagle Scout, I should had known better.
As I sunk further into my seat, I began to see a 'Simpsons' like world release in front of me. Visually, I could see the houses, mentally, characters in 'Simpsons' like form appeared to me in my mind, speaking gibberish, laughing and disappering.
Then, it stopped. I was fazed and in complete disorientation. I didn't know why I was in the car with Weazel and had no idea where time had went.
We later discussed our stories whereas our trips had seemingly been synchronized as far as stages went. I had appeared the same to him as he had to me. He also witnessed some rather perplexing visuals that also seemed to run upon the same context of my trip. The only thing different is that he saw cartoon gingerbread men dancing on the dashboard of the blazer. Yes, it seemed as if he was being laughed at also. It was all very much humorous, but very perplexing. In the end, we went on to experience much more...which will probably be written about at a later time. Until then, Weazel and I have have some more Salvia to try.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Variational inference
In the last chapter, we saw that inference in probabilistic models is often intractable, and we learned about algorithms that provide approximate solutions to the inference problem (e.g. marginal inference) by using subroutines that involve sampling random variables. Most sampling-based inference algorithms are instances of Markov Chain Monte-Carlo (MCMC); two popular MCMC methods are Gibbs sampling and Metropolis-Hastings.
Unfortunately, these sampling-based methods have several important shortcomings.
- Although they are guaranteed to find a globally optimal solution given enough time, it is difficult to tell how close they are to a good solution given the finite amount of time that they have in practice.
- In order to quickly reach a good solution, MCMC methods require choosing an appropriate sampling technique (e.g. a good proposal in Metropolis-Hastings). Choosing this technique can be an art in itself.
In this chapter, we are going to look at an alternative approach to approximate inference called the variational family of algorithms.
Inference as optimization
The main idea of variational methods is to cast inference as an optimization problem.
Suppose we are given an intractable probability distribution . Variational techniques will try to solve an optimization problem over a class of tractable distributions in order to find a that is most similar to . We will then query (rather than ) in order to get an approximate solution.
The main differences between sampling and variational techniques are that:
- Unlike sampling-based methods, variational approaches will almost never find the globally optimal solution.
- However, we will always know if they have converged. In some cases, we will even have bounds on their accuracy.
- In practice, variational inference methods often scale better and are more amenable to techniques like stochastic gradient optimization, parallelization over multiple processors, and acceleration using GPUs.
Although sampling methods were historically invented first (in the 1940’s), variational techniques have been steadily gaining popularity and are currently the more widely used inference technique.
The Kullback-Leibler divergence
To formulate inference as an optimization problem, we need to choose an approximating family and an optimization objective . This objective needs to capture the similarity between and ; the field of information theory provides us with a tool for this called the Kullback-Leibler (KL) divergence.
Formally, the KL divergence between two distributions and with discrete support is defined as
In information theory, this function is used to measure differences in information contained within two distributions. The KL divergence has the following properties that make it especially useful in our setting:
- for all .
- if and only if
These can be proven as an exercise. Note however that , i.e. the KL divergence is not symmetric. This is why we say that it’s a divergence, but not a distance. We will come back to this distinction shortly.
The variational lower bound
How do we perform variational inference with a KL divergence? First, let’s fix a form for . We’ll assume that is a general (discrete, for simplicity) undirected model of the form
where the are the factors and is the normalization constant. This formulation captures virtually all the distributions in which we might want to perform approximate inference, such as marginal distributions of directed models with evidence .
Given this formulation, optimizing directly is not possible because of the potentially intractable normalization constant . In fact, even evaluating is not possible, because we need to evaluate .
Instead, we will work with the following objective, which has the same form as the KL divergence, but only involves the unnormalized probability :
This function is not only tractable, it also has the following important property:
Since , we get by rearranging terms that
Thus, is a lower bound on the partition function . In many cases, has an interesting interpretation. For example, we may be trying to compute the marginal probability of variables given observed data that plays the role of evidence. We assume that is directed. In this case, minimizing amounts to maximizing a lower bound on the log-likelihood of the observed data.
Because of this property, is called the variational lower bound or the evidence lower bound (ELBO); it often written in the form
Crucially, the difference between and is precisely . Thus, by maximizing the evidence-lower bound, we are minimizing by “squeezing” it between and .
On the choice of KL divergence
To recap, we have just defined an optimization objective for variational inference (the variational lower bound) and we have shown that maximizing the lower bound leads to minimizing the divergence .
Recall how we said earlier that ; both divergences equal zero when , but assign different penalties when . This raises the question: why did we choose one over the other and how do they differ?
Perhaps the most important difference is computational: optimizing involves an expectation with respect to , while requires computing expectations with respect to , which is typically intractable even to evaluate.
However, choosing this particular divergence affects the returned solution when the approximating family does not contain the true . Observe that — which is called the I-projection or information projection — is infinite if and :
This means that if we must have . We say that is zero-forcing for and it will typically under-estimate the support of
On the other hand, — known as the M-projection or the moment projection — is infinite if and . Thus, if we must have . We say that is zero-avoiding for and it will typically over-estimate the support of .
The figure below illustrates this phenomenon graphically.
Due to the properties that we just described, we often call the inclusive KL divergence, while is the exclusive KL divergence.
Mean-field inference
The next step in our development of variational inference concerns the choice of approximating family . The machine learning literature contains dozens of proposed ways to parametrize this class of distributions; these include exponential families, neural networks, Gaussian processes, latent variable models, and many others types of models.
However, one of the most widely used classes of distributions is simply the set of fully-factored ; here each is categorical distribution over a one-dimensional discrete variable, which can be described as a one-dimensional table.
This choice of turns out to be easy to optimize over and works surprisingly well. It is perhaps the most popular choice when optimizing the variational bound; variational inference with this choice of is called mean-field inference. It consists in solving the following optimization problem:
The standard way of performing this optimization problem is via coordinate descent over the : we iterate over and for each we optimize over while keeping the other “coordinates” fixed.
Interestingly, the optimization problem for one coordinate has a simple closed form solution:
Notice that both sides of the above equation contain univariate functions of : we are thus replacing with another function of the same form. The constant term is a normalization constant for the new distribution.
Notice also that on right-hand side, we are taking an expectation of a sum of factors
Of these, only factors belonging to the Markov blanket of are a function of (simply by the definition of the Markov blanket); the rest are constant with respect to and can be pushed into the constant term.
This leaves us with an expectation over a much smaller number of factors; if the Markov blanket of is small (as is often the case), we are able to analytically compute . For example, if the variables are discrete with possible values, and there are factors and variables in the Markov blanket of , then computing the expectation takes time: for each value of we sum over all assignments of the variables, and in each case, we sum over the factors.
The result of this is a procedure that iteratively fits a fully-factored that approximates in terms of . After each step of coordinate descent, we increase the variational lower bound, tightening it around .
In the end, the factors will not quite equal the true marginal distributions , but they will often be good enough for many practical purposes, such as determining .
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The site that I am setting my goal for tracking is CM Foodies
My goal is to track users engagement on my site/subpages, I would like to see if any users will engage at least 5 minutes or more on my site/subpages.
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What I've learned up to this point from the data are the goal I set up to get users stay on my site for at least five minutes or more failed and that I need more and better contents on my site to keep the users stay longer. The average user engage on the site for only about one minute, that is four minutes short of my goal of five minutes.
At this point I did not or haven't made any changes to the content of my experiment to improve users engagement.
The process of setting up the content experiment (goal experiment) is not too bad, at first I don't know if I've set up correctly to collect the data of users engagement of the site. I am not sure if my setting is correct for Google anylytics to record and track users that stay at least 5 minutes or more on my site.
In order to test if my goal experiment is set up correctly, I ask my niece to try the site and stay for at least 5 minutes and longer to see if my users engagement experiment will record and track correctly. After a few days have passed I check the data but don't see any data of users engagement of 5 minutes or more recorded.
The two pages with the most views are the Italian and Asian page.
To improve on users engagement, I will need more and better contents to the site such as more pictures, more details in the reviews and possibly actual customers review in additionl to my own reviews.
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RDBMS Concepts and types
Structure of a Table
Entity Relationship Diagram (ERD)
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Read through pages 4-10 in this material
Latentview internal content
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Conservationists say that we are in the middle of the sixth mass extinction due to human activity in the last couple centuries. Wildlife reports have concluded the following things:
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LIVE NUDE GIRLS UNITE! A film review by Steve Rhodes Copyright 2000 Steve Rhodes RATING (0 TO ****): ***
Some people spend time thinking about unions. A lot of people spend time thinking about sex. Very few of us combine these thoughts, but directors Vicky Funari (PAULINA) and Julia Query do in their fascinating peek into the labor struggles of a group of sex workers, a.k.a. strippers, at by-the-quarter peep shows. LIVE NUDE GIRLS UNITE! tells the inside story of the well publicized organizing effort by the sex workers at the Lusty Lady in San Francisco, which, we are told, has mainly female owners and managers.
Julia Query, a stripper as well as the co-director, is one of the documentary's central characters. A writer and stand-up comic, she was a "professional dominatrix" prior to becoming a stripper. As the story opens, a girl, representing the younger Julia, draws in a coloring book about Dr. Martin Luther King. Julia fancies herself as a major activist for justice like her mother, a doctor who has dedicated her career to the betterment of the lives of prostitutes through proper health care.
The documentary features lots of full frontal nudity, as would be expected. This could be criticized in that it does raise the titillation factor, but, without it, it would be hard to imagine exactly what goes on behind the glass curtain. Basically, the women work in a large tank, dancing and cavorting while men on the other side of the glass perform solo sex in little booths. Yes, it is as sleazy as it sounds. The women, however, are frequently mothers and college graduates who look upon their time dancing together as something between a girl's slumber party and a grueling day of hard physical labor.
What motivated the workers to be the first in their industry to organize were the working conditions. At the top of their complaint list was the treatment of sickness. Most companies allow sick workers to stay at home, but not the Lusty Lady, which is typical according to the film.  To avoid such penalties, a woman was required to find a replacement who had breasts at least as large as hers and skin at least as white. A secondary issue for them was scheduling based on race, since management believed that the men preferred blonde Caucasians. Their reasoning was that blonde Caucasians were by far and away the most popular choice for porn video sales.
Once the workers go on strike, they think up some of the funniest slogans and chants you can imagine to popularize their cause. Most, however, are unprintable. One that is printable appeared on a button: "Bad Girls Like Good Contracts." They also had one of the more unusual job actions in the history of labor fights. They tried keeping their legs closed while dancing in order to discourage the patrons.
The last third of the movie concerns the offers and counteroffers during the negotiations between union and management. It is intriguing but covers more traditional material. The only questionable choice the documentarians made was to include some simple cartoon figures to illustrate some of their points. They are funny and cute, but the women themselves are more interesting.
When asked to summarize her job as a stripper, one of them says simply, "boring!" This is something that could never be said of LIVE NUDE GIRLS UNITE!, a mesmerizing examination of a world that most of us have never seen and never will. The film also provides your one opportunity to say to someone, the ticket seller in this case, "I'd like Live Nude Girls, please."
LIVE NUDE GIRLS UNITE! runs a fast 1:20. It is not rated by the MPAA but would be rated NC-17 for graphic nudity and strong language. It would be acceptable for college students.
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--- layout: page title: Projects header-img: "img/about-bg.png" ---
| APPLICATIONS | LINKS | TECHNOLOGIES USED | VIDEO WALKTHROUGH |
|---|---|---|---|
| Rails Restaurant App with jQuery Front End (Updated restaurant app using jQuery) |
|
||
| Rails Restaurant App (The ideal managing app for rating and reviewing restaurants) |
|
||
| Sinatra Bookmark App (A handy way to create and organize your favorite websites) |
|
||
| Eight O'Clock Coffee CLI Gem (Interactive app for java lovers to browse numerous coffee varieties) |
|


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HTML - the basis for all web pages
HTTP - the protocol used between the internet and servers to communicateHTML uses markup tags. Tags include:
Name
b (bold)
em (emphais) = italics
HTML elements can have attributes. Examples include linking to websites like this.
Images use the img tag. Use alt="text" for blind screenreaders. Img is an example of a "void" tag, i.e. it does not have a closing tag.
Inline tag examples include a, span, br, img, and strong.
Block tag examples include div, p, and form. Block elements form an invisible box around them.
.


AJAX; Asynchronous JavaScript And XML; is the most commonly used term in Web Development. For those who are aware of AJAX, its not a problem; but for those who are beginners of web development face the problem in understanding and working with the AJAX.
Asynchronous JavaScript and XML (AJAX) is a set of things working together to achieve a rich internet browsing experience. AJAX does so by enabling the developer to load the page sections asynchronously from the server without making user to wait for the page to be loaded completely.
Now as the request is sent; we will wait for the response and check whether the request is completed and with proper response. So for this there is a event handler for this “onreaystatechange” which will be triggered everytime when there is a change in the ready state “readyState“. The following can be the possible values of the readyState
| 0 | UNINITIALIZED | The object has been created, but not initialized (the open method has not been called). |
| 1 | LOADING | The object has been created, but the send method has not been called. |
| 2 | LOADED | The send method has been called, but the status and headers are not yet available. |
| 3 | INTERACTIVE | Some data has been received. Calling the responseBody and responseText properties at this state to obtain partial results will return an error, because status and response headers are not fully available. |
| 4 | COMPLETED | All the data has been received, and the complete data is available in the responseBody and responseText properties. |
Now along with that we can handle the responses received from the sever. To handle the response status property of the XMLHttpRequest (xhr) object is used. Some of the HTTP status codes are as follows:
A full info on HTTP status codes can be found on following URLs:
| Code | Code Description |
|---|---|
| 200 | The request is OK (this is the standard response for successful HTTP requests) |
| 400 | The request cannot be fulfilled due to bad syntax |
| 404 | The requested page could not be found but may be available again in the future |
| 500 | A generic error message, given when no more specific message is suitable |
| 502 | The server was acting as a gateway or proxy and received an invalid response from the upstream server |


Low Income Scheme applications
25
Total applications
11
To complete
9
Pending
5
Printed
| Date received | Reference number | Name | Date of birth | Postcode | Status | |
|---|---|---|---|---|---|---|
| 01/01/2018 | 56743897 | Shiela Green | 02/04/1984 | NE12 A34 | Printed | |
| 01/01/2018 | 61947226 | Donna Goodman | 15/07/1982 | BD12 4WL | Printed | |
| 01/01/2018 | 30423535 | Brigitte Cantu | 22/06/1949 | GL54 0RU | To do | |
| 01/01/2018 | 69808437 | Victoria Ruddell | 09/10/1972 | EX31 0JA | To do | |
| 01/01/2018 | 70085168 | Dora Ditullio | 23/08/1962 | HP10 2ZU | To do | |
| 01/01/2018 | 22238522 | Patrick Turner | 07/11/1971 | SP4 2PS | To do | |
| 01/01/2018 | 21567562 | Naveen Kumar | 24/05/1985 | LN8 8PE | Pending | |
| 01/01/2018 | 92673985 | Leroy Dennis Gill | 13/04/1956 | S74 8SQ | Printed | |
| 01/01/2018 | 14991422 | Liam Dobson | 02/04/1984 | TR3 5BS | To do | |
| 01/01/2018 | 55951057 | Jessica Randall | 11/05/1960 | SA63 1EA | Pending |


| MultiMarkdown | Result |
|---|---|
| This text is **bold**. | This text is bold. |
| This text is also __bold__. | This text is also bold. |
| This text is *italicized*. | This text is italicized. |
| This text is also _italicized_. | This text is also italicized. |
| `This is some code.` | This is some code. |
| This is a rather long section of code taking multiple lines |
This is a rather |
| MultiMarkdown | Result |
|---|---|
| Link to [Google](http://google.com). | Link to Google. |
| Link to <http://google.com>. | Link to http://google.com. |
| Link to [Google][] with attributes later in the document. Another Link to the [search engine][Google]. [Google]: http://google.com "The Google!" style="border: solid black 1px;" target="_blank" |
Link to Google with attributes later in the document. Another link to the search engine. |
| Send me an email at<EMAIL_ADDRESS>| Send me an email at<EMAIL_ADDRESS>|
| MultiMarkdown | Result |
|---|---|
| # First Header | First Header |
| ## Second Header ## | Second Header |
| ### Third Header | Third Header |
| MultiMarkdown | Result |
|---|---|
| Here is the a normal paragraph. > This is the first level of quoting. >> This is nested blockquote that runs onto the next line. > Back to the first level. Notice the spaces when we start a new paragraph or separate the different blockquotes. |
Here is the a normal paragraph.
Notice the spaces when we start a new paragraph or separate the different blockquotes. |
| MultiMarkdown | Result |
|---|---|
| This is the simplest example of an ![image](mmd.png) embedded in a paragraph. | This is the simplest example of an embedded in a paragraph. |
| This is an image example with a title attribute ![Alternate Message](mmd.png "This is a title") embedded in a paragraph. | This is an image example with a title attribute embedded in a paragraph. |
| This is the same image ![image3][] but with the attributes placed later on in the document. [image3]: mmd.png "This is where the title goes" height=22px width=60px |
This is the same image but with the attributes placed later on in the document. |
When an image is placed in a paragraph by itself, it is wrapped in a <figure> tag. ![This is the figure caption][fig_id] [fig_id]: mmd.png "This is where the title goes" height=45px width=120px |
When an image is placed in a paragraph, it is wrapped in a <figure> tag. |
| MultiMarkdown | Result |
|---|---|
|
* Milk * Bread * Cheese * Cheddar * Camembert * Rice |
|
|
1. Milk 2. Bread 3. Cheese 1. Cheddar 2. Camembert 4. Rice |
|
| MultiMarkdown | Result | ||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Here is as example of [table][simple_table] followed by a more complex [example][reference_table] from the [documentation](https://github.com/fletcher/MultiMarkdown/wiki/MultiMarkdown-Syntax-Guide "MultiMarkdown Syntax Guide")| First Header | Second Header | Third Header | | :----------- | :-----------: | -------------------: | | First row | Data | Very long data entry | | Second row | **Cell** | *Cell* | [simple_table] | | Grouping || | First Header | Second Header | Third Header | | ------------ | :-----------: | -----------: | | Content | *Long Cell* || | Content | **Cell** | Cell | | New section | More | Data | [Prototype table][reference_table] |
Here is as example of table followed by a more complex example from the documentation
|
| MultiMarkdown | Result |
|---|---|
| Here is some text containing a footnote[^somesamplefootnote]. You can then continue your thought... [^somesamplefootnote]: Here is the text of the footnote itself. Even go to a new paragraph and the footnotes with go to the bottom of the document[^documentdetails]. [^documentdetails]: Depending on the final form of your document, of course. See the documentation and experiment. This footnote has a second paragraph. |
Here is some text containing a footnote[1]. You can then continue your thought… Even go to a new paragraph and the footnotes with go to the bottom of the document[2]. |
| MultiMarkdown | Result |
|---|---|
| You can place a link to a point in your document like this [one][], or [another][] place in the doc. ## one ## A simple subheading in a larger document with the same name as the referring tag. ## Another place in the document [another] ## Another place in the document that is referenced by the [another] tag in the heading |
You can place a link to a point in your document like this one or another place in the doc. oneA simple subheading in a larger document with the same name as the referring tag. Another place in the documentAnother place in the document that is referenced by the [another] tag in the heading |
| MultiMarkdown | Result |
|---|---|
| Let's cite a fake book.[p. 42][#fake] [#fake]: John Doe. *A Totally Fake Book*. Vanity Press, 2006. |
Let’s cite a fake book.[p. 42, 1]
|
| MultiMarkdown | Result |
|---|---|
When you are making you definitions you should note the white space.
Apple : Pomaceous fruit of plants of the genus Malus in the family Rosaceae. Also the makers of really great products. Banana : 1. A delicious fruit that can be hazardous if left on the ground. 2. A fruit that comes with it's own packaging Orange : The fruit of an evergreen tree of the genus Citrus. |
When you are making you definitions you should note the white space.
|
| MultiMarkdown | Result |
|---|---|
| \\[ {e}^{i\pi }+1=0 \\] | |
| A formula, \\( {e}^{i\pi }+1=0 \\), inside a paragraph. | A formula, , inside a paragraph. |
| MultiMarkdown | Result |
|---|---|
| Let's reference a glossary term.[^glossary] [^glossary]:glossary: Glossary A section at the end ... |
Let’s reference a glossary term.[1]
|
MultiMarkdown Syntax Guide
https://github.com/fletcher/human-markdown-reference
Based on the Human Markdown Reference by Édouard Brière.
https://github.com/edouard/human-markdown-reference
Modified for MultiMarkdown syntax by the MMD Community.
For the first interaction examples were used from the following websites.


Preparation time
over 2 hours
Cooking time
10 to 30 mins
Serves
Serves 6-8
Dietary
Homemade lemon curd is a thing of beauty. Layer it with meringue and you have a showstopper of a cake!
For the meringue, preheat the oven to 150C/300F/Gas1.
Whisk the egg whites in a bowl until soft peaks are formed when the whisk is removed.
Gradually add the sugar and continue to whisk until soft peaks are formed again. Spoon into a piping bag fitted with a small plain nozzle.
To make a template, draw four 20cm/8in diameter circles onto baking parchment and place on a baking sheet.
Starting in the centre of each circle, pipe the meringue in a spiral to fill the circle, keeping the meringue height as low as possible.
Cook in the oven for 20 minutes.
Turn the oven off but leave the meringues in there for at least two hours. When crisp, remove from the oven and leave to cool.
For the lemon curd, place the lemon zest, juice, butter and sugar into a bowl set over a pan of simmering water. (Don’t let the bowl touch the water).
Whisk occasionally until the sugar is completely dissolved then beat in the eggs and whisk until thickened and cooked through.
Remove from the heat and allow to cool completely.
Whisk the double cream in a large bowl until soft peaks form when the whisk is removed, then fold in the lemon curd and mix gently.
Spoon into a piping bag and snip the end off, giving a width of about 1.5cm/½in.
To assemble the cake, place a meringue disc onto a serving plate.
Pipe the lemon curd cream in a spiral onto the meringue to cover totally.
Place another meringue disc on top and repeat with the cream.
Repeat with the remaining meringue and cream, finishing with meringue on top.
Decorate with the fruit and serve in wedges.


This tests Indent on a selection that ends at the start of a paragraph. Since we don't paint the gap before the paragraph for most selections like this, we don't perform Indent on the paragraph that the selection ends in.
This paragraph should be indented.
This paragraph should not be indented.


12. Try GET endpoint to check current status of the cancellation authorisation.
13. Try GET endpoint to get current payment status (in should be `CANC`, cancelled).


Facio is designed to be flexible to how you bootstrap your projects, heres how to use it.
Facio used via the command line, after installation you should have a facio command available. Use help to see the options available.
$ facio -h
To create a new project its simple, cd into the directory you want your new project to live, facio will create the directory for you so you don’t need to make it, for example:
$ cd /home/me/projects
$ facio -n hello_world
This will create a new hello_world directory at /home/me/projects and inside the default facio template will have been processed and placed there.
Facio is designed to be flexible, with a combination of command line options and a configuration file.
| --version | show program’s version number and exit |
| -h, --help | show this help message and exit |
| -n <ARG>, --name=<ARG> | |
| The Project Name (Mandatory), only use alphanumeric characters and underscores. |
| -t <ARG1>, --template=<ARG1> | |
| Path to your custom template, absolute paths only, git repositories can also be specified by prefixing with git+ for example<EMAIL_ADDRESS>| |
| -c, --choose_template | |
| If you have more than 1 template defined use this flag to override the default template, Note: specifying -t (–template) will mean this flag is ignored. | |
| -s <ARG>, --template_settings_dir=<ARG> | |
| Template settings directory name | |
| --vars=<ARG> | Custom variables, e.g –vars hello=world,sky=blue |
| -i, --install | Install the project onto your path, e.g python setup.py develop |
| -e, --venv_create | |
| Create python virtual environment | |
| -p <ARG>, --venv_path=<ARG> | |
| Python virtualenv home directory | |
| -S, --venv_use_site_packages | |
| Create python vittual environment without –no-site-packages | |
| -x <ARG>, --venv_prefix=<ARG> | |
| Virtual environment name prefix |
Most things you can specify as command line options are also configurable in a facio.cfg file, this should live in your home directory and be prefixed with a ., for example /home/you/.facio.cfg.
The ~/.facio.cfg file uses ini style formatting.
[template]
# The Default Template to user (can be a git repp, prefix with git+url_to_repo
default=/home/me/my_custom_template/
# Add other templates here, for example:
experimental_template: /my/new/template/
flask<EMAIL_ADDRESS>[misc]
install=0 # Experimental
# Experimental
[virutalenv]
venv_create=1
venv_path=/home/me/.virtualenvs/
Above is an example ~/.facio.cfg file and contains a [misc], [virtualenv], and [template] sections. These sections and their allowed options allow you set defaults so when you run facio form the command line you need to keep specifying things like template path and virtual environment creation.


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I'm an independent graphic designer that's eager to integrate creative and innovative designs and concepts into your personal or professional projects.
I'm an independent graphic designer that's eager to integrate creative and innovative designs and concepts into your personal or professional projects.
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Leer más...Testimonials are short quotes from people who love your brand. It's a great way to convince customers to try your services.
Testimonials are short quotes from people who love your brand. It's a great way to convince customers to try your services.
Testimonials are short quotes from people who love your brand. It's a great way to convince customers to try your services
Some quick example text to build on the card title and make up the bulk of the card's content.
Ver proyectoSome quick example text to build on the card title and make up the bulk of the card's content.
Ver proyectoSome quick example text to build on the card title and make up the bulk of the card's content.
Ver proyectoSome quick example text to build on the card title and make up the bulk of the card's content.
Ver proyectoSome quick example text to build on the card title and make up the bulk of the card's content.
Ver proyectoSome quick example text to build on the card title and make up the bulk of the card's content.
Ver proyecto| # | First | Last | Message |
|---|