Friday, August 26, 2016

Happy Hips, Peaceful Pelvis

I recently read an article about stretching for seniors.  The author said that as we age our muscles become shorter and lose elasticity. True, but why?  In short, too much adult-ing:  we sit more and move less, and, we have been doing it for 30, 40, 50, 60 years.
 Both of these can affect the structure of your bones and muscles.  We need to move, but the trick is to do it safely so that we can do whatever type of exercise we like.

So, what do the hips and pelvis have to do with each other?

Well, take a look at the diagram on the right. This is a picture of the pelvic floor,  which shows the muscles we tighten when we do “kegel” exercises (you know, pretend that you have to urinate and stop it.) Many of us still do the tightening now,  all the time, even though our baby is 35 years old.  So how come even though we’ve been diligently squeezing at stoplights for years we now have dribbling and pain during sex?  It’s because these muscles are now are not only weak, but tight.  What do you think would happen to your biceps if you held your elbow closed for 35 years?

Muscle strength comes from being able to shorten a lengthened muscle.  If the muscle is already short, it can’t get any shorter or stronger.   Also, notice how close your hips are to the muscles in your pelvis:  the hip socket is above the pelvis and to the side. Some of the muscles that move your hip come from your pelvis and vice versa.  If one is tight and weak, the other is too. These muscles are not only related to your hips, but to your back, knees, and feet. If you are overusing or holding one area, chances are that you’re doing it elsewhere, too.

How many of you have been stretching your hamstrings for 25-plus years before running, walking, yoga, or dance?  Is it working?  Do your hamstrings, in the back of your hip, or your muscles in the front of your thigh, ever get longerNo they do not. They get tighter.  There is a difference between stretching and elongating…and that’s the key difference between exercise and health.

Movement Teacher, Beth Rubenstein MS, PT, Guild Certified Feldenkrais Practitioner

Come find out how to make your pelvic muscles more effective as you age.  Discover how to guide yourself in a gentler way so you can alleviate pain and stiffness while moving with ease and joy!

Go here to sign up :

Friday, August 19, 2016

Brain Changing Class

I’m taking a Changing My Brain class!

Some people, however, call this class TAP.

Anyway, I can’t wait to tell you about this class!  An admitted baby boomer herself, Deborah Perez is a beautiful dancer and an excellent teacher.   We do our shuffle-ball-changes at  By Your Side Dance Studio in Culver City and she is by far one of the best dance teachers I have ever had.  She is able to adjust her teaching so that it’s unique to all of her students; making each one feel as if they’re getting a private lesson.  We have former dancers, young and strong new-comers, and me: a 65-year-old, semi –coordinated, would-be dancer and gymnast.

I’ve always loved dancing.  I love ballroom because I can turn off my brain and pretend I’m a tall, long-legged dance diva.  Not so with tap.  This style of dance requires you to tune in, turn on, and tap up!

Tapping appears to be the perfect path to fitness of body and brain.  It’s not unlike what I have experienced in my 25 years as a Feldenkrais® teacher; we like to think of ourselves as “neuroplasticians” because our work can change the way people think, feel, and act.   According to Norman Doidge in his latest book, The Brain’s Way of Healing, neuroplasticity is the “property of the brain that enables it to change its own structure and functioning in response to activity and mental experience. “  We used to think the brain and central nervous system was set once we reached the age of 25, but Doidge now believes that in order to  “enable neuroplasticity to happen, the approach must require the active involvement of the whole patient in his or her own care: mind, brain, and body.”

I think I am definitely in the process of transforming my mind and brain, and (with a little luck) my body.

I am tapping into the unknown; sometimes this dance can be confusing and just plain hard.  For instance, I was already aware of my toe clenching habit but you sure can’t do that in tap without developing pain almost instantly!  So it forces me to be constantly aware of where I am on my feet.  This requires the participation of my brain and muscles which in turn means constant challenges to my balance.  I have to stay upright, relax my feet, move in a circle and keep my hand aloft while slapping, spanking, shuffling, and ball stepping.

Talk about challenging!

One of the ways we encourage neuroplasticity in the Feldenkrais Method® is by using novelty.  Awareness Through Movement lessons are full of “novel” movements.  We “wake up” the brain (and therefore new neural pathways) by bringing our awareness to parts that move together.  That’s what happens in tap!  In every lesson, we learn something novel.  I have learned the “Buffalo,” the “Irish,” the “Grapevine,” and loads more.  And then there is memory.  I can feel my brain growing as I learn the moves and then put them into a sequence. A strategy thay my teacher recommends is letting the music tell us what’s next.

Of course, all of this requires strength and endurance.  My legs are not as strong as they used to be and I don’t have the muscle fibers I once had.  As I Feldenkrais teacher I know that if I move just from my feet, I won’t last long in this vigorous dance.  I must engage my whole self.  If I don’t, I won’t get through the hour class without being debilitated.  If I do, I’ll feel invigorated!

So: awareness, novelty, strength, endurance, and memory.    Tap wakes up your brain and your body by using all of these and I have to tell you that along with my work as a Feldenkrais teacher, I feel like I have found just the right combination of body and brain exploration. I can feel those neurotransmitters transmitting!!

I have now found another love besides the gentle, lovely movement I do when I lie on the floor for an Awareness Through Movement® lesson.  My ability to tune into my movement and find another, more suitable way to do it is ingrained in my Feldenkrais® study. Both are keeping me young (and relieving my guilt about hating crossword puzzles and Sudoku!)

Deborah Perez of By Your Side Dance StudioBy Your Side Dance Studio and your happy, dancing Feldenkrais teacher!

“Movement is Life, without movement, life would be unthinkable.”
M.Feldenkrais DSc

Tapping along until next time,

Friday, July 29, 2016

More on Multiple Sclerosis # 3

More but not the end......

There are four primary types of MS; relapsing-remitting, secondary-progressive, primary-progressive, and progressive relapsing.  But even though there are common factors among those with MS, everyone is an individual. That means there’s no cookie cutter approach to increasing function.

Still, there are similarities, so let’s consider them here…

In my last two posts, I touched on how we approach the issues of knowing where we are in space, spasticity, coordination, and balance.spasticity, coordination, and balance   Here, we’ll look at heat and stress, fatigue, and flexibility.

Heat can cause a temporary worsening of MS symptoms and stress and tension can raise core body temperature. With the gentle movement of a Feldenkrais® lesson, a participant can learn to release stress and tension.  This helps turn down the heat while allowing body energy to flow freely. By using attention and breath, one can learn to detect (and thereby avert) increased body temperature *before* problems begin.

Living with MS can mean change and stress. Stress depletes an individual both emotionally and physically and adds to fatigue to boot.  Using the Feldenkrais Method® helps those with MS learn how to function in a more relaxed state, thus quieting the sympathetic nervous system (your “fight or flight” response.) Since the movements are based on functional activities, people are given the opportunity to notice their habitual anxiety patterns and to explore more effective ways to cope. While teaching regular classes for the MS Society, we frequently met in less than optimal facilities.  There was often noise or movement in the room, but I chose not to change the location of these sessions because I knew my students needed to learn to calm and sense themselves in all surroundings.  After all, malls, noisy restaurants, and traffic jams don’t go away just because you have MS!

Fatigue can be the biggest challenge because we can create it without even knowing it.  Strain, tension, and fatigue are often the result of smaller muscles doing the work of larger ones. Learning does not occur when fatigue is present, so students are given the opportunity to modulate their own sense of fatigue.  Because participants are able to move or rest at their own pace, they gain more control over fatigue.

Flexibilty is the ability to switch and use a different part of the body for an activity.  Learning to use muscles to move rather than to support will improve range of motion and aid in increasing energy.  Initiating motion from large muscles closer to the center of our bodies also allows for more proportional distribution of movement, and that conserves energy and strength.  Those are the keys to maintaining the joint and muscle flexibility that is important for walking and other daily living activities.

Although I accommodate all ability levels and use many positions, I like lessons on the floor because it helps people feel and sense in a different way and explore what works.  This enables students to discover a new way to walk, get up from the floor, or play with a child.  I teach my student to notice what is happening.

I ask students to do less than they can so that they can focus on learning how to be their own “inner advisor”.  Once moving becomes easier, they naturally want to do more.

Comment or ask questions here, or contact me at

Keep exploring and keep asking questions,

Friday, July 15, 2016

More About How I work with Multiple Sclerosis

Let’s get more specific about what I do for people with Multiple Sclerosis

In my last blog, I wrote about how the Feldenkrais Method® can benefit people with Multiple Sclerosis (MS). This blog will be the second of 3 blogs about MS and will get into more details for folks who would like more information.

Most people don’t ever think about what they do or how they move, that is until movement becomes a little harder.  When we slow down and pay attention to how we move and what we do, we are able to fine tune our movements and actions.  In other words as Moshe Feldenkrais said, “If you don’t know what you do, you can’t do what you want.”  This is exactly what we learn when we practice the Feldenkrais Method®.

If you have MS, or know somebody who does, (there are approximately 200,000 people in the US and 2.5 million worldwide with MS) then you know about some of the debilitating symptoms. Because the symptoms are so varied, when working with MS, one must have a clear understanding of the interweaving nature of the brain and body. One cannot “correct” one part without affecting the others.  We cannot change walking if we don’t work on breathing or knowing where we are in space. The Feldenkrais Method® is based on connections of parts and the whole and how they work together and separately.

I will use the example of walking and in this blog, I will cover 4 symptoms of MS and how I work with them.  I will cover 4 more in my next blog.  Some of the words I use may not be familiar to you, but if you have MS, or know MS, you know what these words are.

Walking is the primary reason that people with MS come to my practice.  What do you need to be able to walk?  We will start with an awareness of where your body parts are in space. In medical language, this is called kinesthetics/proprioception.  I take you through a series of movement sequences, either verbally or by touching you.  These very gentle, easy movements allow you to relax.  When you become relaxed you can explore the movement. You can become aware of movement patterns that are holding you back. You can learn how to abandon habitual movement patters that are not working.  No doubt, they used to work, but not now.  Through the subtle movement lessons, one can develop awareness, leading to flexibility and coordination.

Another symptom that makes walking difficult is spasticity. Spasticity is a state where certain muscles are contracted at all, or inappropriate times.  The Feldenkrais Method® encourages students  to move with little effort, enabling them to stop or reverse any movement before the muscles can become excited or overexcited.  Movements are slow, gentle, and safe. You will be better able to modulate the how your muscles begin action. You now will be allowed to make minor adjustments based on your own perception.

Problems with coordination are quite common among people with Multiple Sclerosis, because of decreased communication within the brain and spinal cord.  Coordination is complicated, at best.  Actions utilize certain muscle sequences.  An example, you bend you knee, and lift your foot before your hip moves your leg forward for walking.  However, before you even move your legs, you see something you want to walk to or for, either in reality or in your imagination. You also have to maintain an upright posture and you must be breathing if you want to move efficiently.   The movement sequences in either modality of the Feldenkrais Method® teaches control of movement in space. This includes the ability to control direction, quality, and speed.

So often people with MS have difficulty maintaining balance.  Through the Feldenkrais Method®, students with MS are given the opportunity to explore “dynamic posture,” where the skeleton carries the weight and the muscles are freed up to move more efficiently.  The relationship between the skeleton and muscles is explored.  Movement through the center of the body is emphasized, rather than holding at the “core.”

My next blog will explore heat sensitivity, fatigue, stress, and flexibility.
Contact me if you would like to talk about yourself or a loved one with MS on Feldenkrais and MS

Do I Work with People with Multiple Sclerosis

The first of three.....

The Feldenkrais Method explores how the brain can change. Multiple Sclerosis is a disease that affects the brain, the nervous system.  I often work with those who have Mulitple Sclerosis, (MS). I have worked with folks with  Multiple Sclerosis but I also have a relationship that’s up close and personal.  While I don’t have the actual condition, it’s been a part of my life since I was four and my father was diagnosed.  The disease took him two weeks after my fourth birthday, on April 30th 1955.  My father's brother, Benjamin (for whom I am named) was diagnosed and died of it in the 1930's.  In 1986, it claimed the life of my sister, Susan.

Multiple Sclerosis has left its indelible mark on my family.

My family has been involved with the MS society for as long as I can remember.  As a small boy, my brother Eli walked house to house with the little box collecting for the MS “hope chest.”  My friends and I put on backyard shows, charging money and donating.  My brother and I remain quite involved and I still write and speak about MS to whoever will listen. My daughters and I have participated in the MS walk every year since they were born.

When I was a young physical therapist in 1976, I started the first class for MS patients at UCLA. In 1991, after I became a  Guild Certified Feldenkrais Practioner® I taught a weekly Awareness Through Movement®class sponsored by the MS Society.

Here’s why I find that the Feldenkrais Method® to be an ideal approach to work with people with Multiple Sclerosis:

Since we know that MS can affect any part of the nervous system that is covered with myelin (the “insulation” covering nerves), any approach to increase function must involve the whole person.  That makes the Feldenkrais Method® a good match; not only because it connects one part of the body to others, but because it involves no stress, increased energy use, pain, or sweat.  Also, it actually can lower an over-heated body temperature by relaxing the “fight or flight” system.

What also makes the Feldenkrais Method® such a great fit for MS is that depending on what type a person has, symptoms can vary widely from day to day.  Since the Feldenkrais Method® is about awareness, how to attain it, and how to use it, the student (patient) is able to assess herself continuously and create her own strategies for change.

The combination of awareness and flexibility is very powerful in combating the effects of this disease. Using muscles to move rather than to support will improve range of motion and aid in increasing energy.  Initiating motion from the large muscles closer to the center of our bodies will allow for a more proportional distribution of movement, thus allowing energy and strength conservation, two major concerns for MS patients. In turn, these components add to the maintenance of flexibility of the joints and muscles that are important for walking and other daily living activities.

All of us have enormous potential for learning, no matter what our physical ability is in any moment.  Learning about awareness, flexibility, and change will  enhance function.

 Think about this for a bit. I have two more blogs coming on this subject.  Contact me with questions or comments

Beth Rubenstein, MS,PT, GCFP

Sunday, April 24, 2016

Posture: What are our Notions

People have many ideas and notions about posture.  I have recently overheard conversations and read facebook posts and am concerned about what people go through to achieve a position that they think will make them look better without any regard for how they feel.

     I would like to share my   FAQ's about Posture  or   Myth vs Reality

1. I have so much trouble standing or sitting straight.  I must be weak.  What muscles should I       strengthen to be able to stand or sit straight?
    Very often we think that if we tighten the muscles of our chest and belly, and of our back, our muscles will hold us up in a straight position. However, the opposite is true.  By doing this, you will have muscles pulling from the front and the back and your spine becomes compressed in the crossfire. When you are not holding so tightly you can feel the lightness and length of your posture. You can feel the pressure on your feet, where it belongs and not in your neck, back, hips,or knees.
2. My mother always told me to "stand straight."   What does that mean?
    Some people think of themselves as a stack of bricks, straight and strong. They are immovable. See myth number 1, 2, and 3.  We are not a stack of bricks. We have brain. Even in the age of "smart" building, a stack of bricks does not have a brain. Bricks, or a building, cannot adjust for the nuances of balance and function. We are moving beings, not static towers.
3. I do loads of sit ups, but still can't stand for more than 10 minutes without pain.  Why is that?
     If your posture creates pain, then it is not working for you. You need to move differently and not stand like a stack of bricks.  Posture is not about strengthening any muscles. It is about how we organize and coordinate the movements of our head, back, hips, arms, and legs. Our anatomical design, as humans allows us to stand upright but we have to allow our muscles to be relaxed and our skeleton, or bony pelvis to support our belly.
4. I try very hard to stand straight. Why does my neck hurt?
    See question # 1.  Our muscles are meant to move us, not hold us. Our neck muscles are very small. They are for quick movement, for scanning our horizon, for keeping us out of danger; they are not for holding our heads up. Heads are heavy.  Again, our anatomical design allows our skeleton to support us and our muscles to move us.
5. How can I stand up for a longer period when I am wearing high heels?
     High heels move our center of gravity forward. If we are aware of our pressure on the feet, it won't matter if we are standing on pebbles, rocks, dirt, sand, or high heels. Again, we have a brain. If we can sense what we need to do and adjust for different situations, as long as we are wearing shoes that fit correctly we can stand in or on any surface.
6. I can't stand or sit for longer than 5 minutes. Everyone says I have beautiful posture. Is it supposed to hurt?
     See question previous questions.  Our posture needs to come from inside of us. It comes from sensing what we are doing and what we might do differently, not from what it looks like on the outside.
7. My mother tells me to pull my shoulders back. Can I wear a band to keep them back?  Or is there an exercise I can do to strengthen my upper back?
     You could wear a band to hold you, but you would probably fight against it the whole time you are wearing it and as soon as you took it off you would revert back to your original posture and be in a great deal of pain. Good posture comes from the inside, not from an outside force.
8.  Sometimes when I sing in the choir, my throat feels tight. I try to hold my head up straight. Is there an exercise I can do to strengthen my neck?
    Again, this has nothing to do with the strength in your neck. We do not sing with our necks. Singing is about breathing and how you control and coordinate all of the muscles involved. It is not about strengthening. You need to hold your head in a way that allows your muscles are soft and your neck is comfortable. A lesson with a trained voice teacher might help you
9. I read about a gadget that I can sit on at work that will teach me to sit up straight. How does that work?  Does it work?
    Our posture is not static. We cannot depend on an outside "gadget" to know what our brain wants to do and when. A quick fix is a way not to pay attention to ourselves. We need to know where we are and where we want to be. This happens  through learning to be aware.
10. What is good posture anyway?
     Posture is not static. In order for your posture to be "good," it has to allow you to move in any direction at any given time. The better question is, "How adaptable is your posture to different situations." What are you standing for- to talk to a loved one, to give speech, to navigate a room full of strangers?  Our posture will be different for all of these activities.

My hope is that these answers will help clear up some common misconceptions about posture.
The key to understanding and improving our posture is to move with ease and grace.

Contact me to learn more about your movement, your balance, how to decrease pain, and creakiness at

Monday, February 29, 2016

Most of us think that balancing has to do with extreme activities.

But we balance all the time.

Every time we step, every time we reach, every time we look up, lift, or run, we use it. As children, our sense of balance is effortless. We roll, swing, climb, and twirl. And we get up and down from the floor with ease as part of normal movement.

But as we age, we start to lose the pathways onto and off of the floor. We get good at sitting still…and not so good at falling.

There are many reasons for our deteriorating balance:  arthritis, neurological issues, busy lives.
The natural tendency is then to hold ourselves more rigidly; which means we can end up compromising natural balance with behaviors that set in before we even know we’ve created them. As Moshe Feldenkrais said, "We don't know what we don't know."

So how do we get back to our childlike ways; when movement was easy and fluid and we worried more about who was “it” than breaking a hip?

We start with self-awareness.

Unconscious movement got you into this mess, conscious movement will help get you out.  Here are four ways we’ll show you how to do that in our Dynamic Balance Workshop:

1.       Smoother Quality of Movement

You’ll learn an increased sense of awareness.  Attention is drawn to the sensations while moving and resting.  This is fundamental to the Feldenkrais Method.® You will become an explorer of your own experience.   Your range of movement possibilities will grow.  You will learn to sense immediately if a part is strained or painful.  You will be able to cultivate a smoother, more comfortable way of moving your muscles and activity will become more efficient.

2.       Improved Skeletal Support
You will learn to use the mechanics of the skeletal system. Muscles move us. But the skeleton is meant to support us.  You don’t need to use your muscles as much to maintain balance or posture if your bones are aligned properly.   Through your own experimentation, your muscles will become freer to move you more efficiently while your bones become free do their job.

3.       Better Coordination

Being able to sense how we are using ourselves means we can learn to be more efficient with all of our daily tasks.  Once we’ve learned how to allow the skeleton to support us, we can start sensing our muscles for more coordinated actions.  We’ll know when to use a specific part and when to give that movement over to another muscle or part. An example of this would be lifting, carrying, or reaching.

4.       Enriched Breathing

Improved breathing means better movement.  Improved movement causes better breathing.  So learn to tune into your breath: are you holding it?  Where do you breathe?  How do you breathe?  When do you breathe?  As we release the inefficiencies in the musculoskeletal system, breathing becomes easier as the ribs, neck, breast bone, clavicles, and belly become free to do their jobs.

Taken together, these steps allow for change from the inside out.  You achieve improved performance through your own observation, exploration, and discovery.   You’ll learn this not by working on individual muscles, but by engaging the nervous system and the brain.

This is the closest we come to the type of learning we do in infancy and early childhood, when we discovered how to move by rolling, crawling, walking, jumping, swinging, and, yes, even falling down.

The good news is that we can work on balance at any time in our lives. We can improve it by sensing and moving efficiently. Through this attention and awareness you can balance yourself to better health!


What were the causes of the Glorious Revolution?

Quick Answer

The Glorious Revolution was a political coup that took place in Great Britain during the mid-17th century; the main cause of this conflict was growing Protestant concern over King James II's strict adherence to his Catholic faith. This conflict is also known as the Revolution of 1688, and it resulted in the solidification of Parliament's power over the monarch and the Catholic King James II being replaced by his daughter, the Protestant Queen Mary, and her husband King William III. Although this was a political conflict that resulted in the deposition of a ruling monarch, it was a relatively peaceful transition in military terms, resulting in little bloodshed.

Continue Reading

Full Answer

Although the Glorious Revolution ended with King James II being replaced by a monarch of his own bloodline and his removal from power didn't result from a violent military conflict, the revolution does represent a foreign invasion of sorts. King William III, Mary's husband and King James II's son-in-law, was a member of the Dutch aristocracy and was known as William of Orange before he took the throne in England. Although the revolution may be referred to as the Bloodless Revolution, Ireland and Scotland responded with force, which led to further revolutionary conflict and much more bloodshed in those two areas.

Learn more about Middle Ages

Related Questions


US and Europe face off over nuclear weapons

A draft version of NATO’s new mission statement released May 17 recommends keeping an estimated 200 US air-dropped gravity nuclear bombs on military bases throughout Europe.

The American warheads are remnants of the Cold War, and many European states, including Germany and Belgium, want them removed.

The nuclear weapons, which are stationed in non-nuclear NATO member states, have remained in the region because they are in line with NATO’s mission to preempt any potential nuclear war.

“They are now re-classified by the US Senate and they can be used against rogue states. Iran and Syria explicitly are targeted with these mini-nukes,” said Michel Chossudovsky, the Director of the Centre for Research on Globalization.

The maintenance of the nuclear weapons in Europe comes at a high cost. Although the political climate in the United States is focused on the reduction of spending and cutting the deficit, this is not a program the US seems poised to cut back.

The expense is a non-issue according to Chossudovsky, who says the weapons are there for security reasons to intimidate the nations in the Middle East.

“It’s not by accident that these weapons are there. They are remnants of the Cold War, but they are deployed in relations with the war on Iran,” he said.

US President Barack Obama has been campaigning heavily for a nuclear free world and the general reduction of nuclear arms globally. Chossudovsky said there is another agenda.

“Obama doesn’t was a nuclear free world. Obama wants to control and have a monopoly over nuclear weapons,” Chossudovsky said.


sanjay thumma

Every thing about TIKYA KEBAB | Vahrehvah :

[caption id="attachment_6071" align="alignleft" width="150" caption="Tikya Kebab"]Tikya Kebab[/caption]

Tikya kebab is a popular classic Bangladeshi dish made with mince meat, channa dal, Indian spies, ginger and garlic etc. This dish is great at barbecues, as snack, starters or main course. Kebabs generally go well with salad, lemon wedges and tandoori chutney.

Tikya kebab made with raw mince meat is simple to prepare and can be ready for eating in a short time. It has a unique and exceptional taste of kebab and is perfect for afternoon tea or Iftar time. Kebab is a wide variety of meat dishes that originated at Persia and later spread to Middle East and Asian countries and now has become popular worldwide.

Kebab generally refers to the shish kebab served on the skewer; however they are many ways of making the kebabs. Kebabs includes grilled, roasted and stewed dishes of large or small cuts of meat or ground meat which may be serve on plates, in sandwiches or in bowls. Traditionally the meat used for kebab is lamb but now may also be beef, goat, chicken, pork, fish and seafood or even vegetarian foods like falafel or paneer.

Kebabs in India are more or less similar to most other kebab preparations having their distinct taste crediting the spices native to the sub-continent. There are a wide range of kebabs that are popularly prepared in most of the small and top restaurant throughout India which include Galouti kebab (These kebabs are flat, pan-fried kebabs and popular for their melt in mouth quality. The mutton mince used to make these is marinated in raw papaya that acts as a tenderizer. They are unique in taste and exquisite even if they are full of fat), Kakori kebab (These are somewhat similar to the galouti as both are tender and just melt in the mouth. Kakori kebabs are longer in shape like seekh kebab, skewered and then roasted), Seekh Kebabs (This was possibly introduced by the Mughals to India, and originally made of beef mince. Of recent days, lamb is used and even chicken (since beef is banned in India), Shami kebab (they are stuffed with fresh mint leaves, finely chopped onions and green chilies) and Hara Bhara kebab being one of the popular vegetarian kebabs.

Generally in a traditional Tikya kebab is made of ground meat, onion, salt, pepper, ginger, garlic, turmeric, chili powder and seasoning. All these ingredients are mixed together until the mixture become smooth and sticky. An egg is added to help the mix stick together. The mixture is flattened and then pan fried till golden brown in color.

To prepare this classic flavorful and delicious Tikya kebab, firstly soak the channa dal overnight and then boil in twice its volume of water. Strain off any excess water. Put the meat, onion, ginger, garlic and spices through a mincer. Mix well and add salt to taste. Add the dal to the mixture and fry in a little ghee for 20 minutes. Add a little water if it dries up too much and leave it aside for about 3 hours or overnight to thicken and dry.

The next day or when ready, add the egg yolk and if it doesn’t hold together add gram flour to thicken or water to thin. Add fresh coriander or parsley. For seekh kebabs, roll mixture in breadcrumbs to sausage shapes. Skewer them and cook over charcoal (best) under the grill or fry in a frying pan or roll into balls and coat in breadcrumbs and deep fry.

To try this recipe, do click on the below link for detailed recipe:

By Vah Group


The historical cost of plant and equipment (not land) is also used to determine the amount of depreciation expense reported on the income statement. The accumulated amount of depreciation is also reported as a deduction from the assets' historical costs reported on the balance sheet. (In the case of impairment, some assets might be reported at less than the amounts based on historical cost.)

The use of historical cost is also a disadvantage to those users of the financial statements who want to know the current values.


You are here

Whistler, Roussel, and Frame Design

Museum visitors ask us lots of excellent questions, but one frequent topic is that of frames. How do we choose them? Are they original? Visitors to Whistler and Roussel: Linked Visions may have noticed that there are several different frames in use in the exhibition. Both James McNeill Whistler and Theodore Roussel cared enough about the public presentation of their prints that they designed special frames to exhibit them. So in keeping with their shared interest in frame design, we made a point to present their works on paper in frames consistent with the aesthetic that each of them preferred. In the case of Whistler’s prints and drawings, we have used frames that were made based on his own designs. Many of these were seen previously at the Art Institute in the 1998 exhibition, Songs on Stone.

For Roussel, whose work has only rarely been shown before at the Art Institute, we were able to use some of the original frames that he himself created. Roussel designed two different types of frames for his prints. For his monochrome prints, he used a thin wooden frame with an ivory or bone-colored finish; this frame style had rounded corners, and Roussel then adhered prints with different patterns to them. One example is his Lily Pattern Frame of 1888/89 (top image). For some of his color prints, Roussel designed elaborate ensembles consisting of the color print or work of art, which was placed on a printed color mount, and then both were enclosed in a wider frame profile with square corners onto which patterned prints were also adhered. There are three of these complete ensembles in the exhibition, including Last Poppies, shown in the Stag and Flower Pattern Frame (image immediately above).

In situations where we didn’t have enough of Roussel’s original frames, we created new frames in order to carry out his vision. In this photograph, you see conservation specialist Christopher Brooks and frame conservator Kirk Vuillemot (left to right) discussing the vintage frames the Roussel produced. We selected the monochrome frame style as our prototype, and we decided to emulate the rounded corners and ivory colored varnish. Kirk developed the reproduction ‘Roussel-inspired’ model that we used in the exhibition. We wanted to be clear that these were not original period frames, so to help make that distinction we did not produce pattern prints to adhere to the frames.

In addition to the specific framing decisions made for the exhibition, special attention was also paid to the overall presentation of the works. For Roussel’s L’agonie des fleurs, we used the new Roussel-style frame and then mounted the work on white-gold leaf coated paper (above). This presentation emulates Roussel’s experimentation with metallic inks for printing and also for printed mounts. We also employed a green-brown mat for some of Whistler’s color prints, like Moonrise in the New Forest (below).

One of the great delights of preparing an exhibition that is based on the Art Institute’s permanent collection is the opportunity to work with conservation preparators like Christine Conniff-O’Shea (below) to make these kinds of decisions. When an exhibition features permanent collection works rather than those borrowed from other institutions, we can control how objects are matted and framed to create a viewing experience that not only enhances the pleasure of seeing our collection displayed but also supports the thesis of the exhibition itself.

—Victoria Sancho Lobis, Prince Trust Associate Curator, Department of Prints and Drawings


Establishing Yourself as Pack Leader

Whether you have just adopted a young pup or an adult dog, you have many things to teach your new companion. You want your dog to be loved, trained and lively, but not spoiled, a robot or uncontrollable. Dogs can be naturals at learning manners and commands, particularly when you understand a key aspect of their nature. Dogs are social, pack-oriented animals. Your dog will respect a strong, clear, fair leader. If you fail to establish this position for yourself, your dog will feel obliged to try to take the position of leader for himself.

The Alpha Role

In a natural state, dogs would live their entire lives within the closely structure social order of their pack. While young, they would begin to learn the workings of the pack's social system and, as they grew, begin to establish their place within the pack's dominance hierarchy. Dominance, submissiveness, leadership, obeying others - these are all concepts that are understood by every dog. These are all concepts that you must understand as well if you are to relate you your dog in a successful manner.

Steps to Establishing Your Role as Alpha

Professional trainers know that it is a waste of time to try to train a dog without first establishing themselves as alpha to the dog. Every dog needs a leader to listen to and adore. Without this leader, a dog will feel lost and unstructured. If you do not take the role of alpha, your dog will be forced to take the role himself. Here are some steps to establishing your role as the alpha. Notice that these involve both behavior and body language - two types of communication that your dog will understand.

1. Always praise your dog as if you own it. Put your hands firmly on the dog. Hug the dog. Pat him so that your hands get warm from the contact. Do not praise him in a timid way.

2. Praise warmly, well and quickly. Do not drag out your praising of a working dog. Do not fawn over the dog just because he did one sit-stay.

3. Reprimand fairly and quickly, then forgive. Don't hold a grudge. When you put your hands on your dog, do it with confidence and authority. Hands on does NOT mean hitting. Hands on may mean a collar shake, a leash correction, a surprising assist into a sit or down. Do it quickly and with authority. Then when you've made the dog do exactly what you want - once - give him a hug. That's alpha.

4. Make the dog obey on the first command. Don't get into the habit of repeating yourself. A dog's hearing is significantly better than yours, and you can bet he heard you the first time.

5. Give commands only if you can follow through, and make sure you always follow through. If the dog is running across the park to meet another dog, do not yell "come" - if he decides not to obey, you have no means of correcting him. Once he accepts you as leader, he will stop and return to you - because he will have learned that leaders are to be obeyed.

6. Give permission. Give it for what is about to do anyway as long as it is OK with you. This does not mean you say OK when you see your dog about to steal a plate of cookies. This means you do say OK when your dog is about to get into the car for a ride with you, eat the food in his bowl, go out with you for his afternoon walk. It means that in a subtle way you are teaching the dog to look to you for approval and permission instead of making decisions on his own. Remember - the better behaved the dog, the more freedom and fun he can have.

7. Deny permission. Monitor your dog's behavior. Teach him some manners. Even if you like him to walk on your couch and coffee table, he shouldn't behave that way in other people's homes. When you take him to the lake, he should wait for permission to swim. It may be too cold some days or there may be too many young children swimming.

9. Be benevolent, but tough. Act like a top dog. Tough, but loving. Always be fair an never get angry. Dogs understand what's fair and what's not.

10. Be a model to your dog. The top dog behaves with dignity, surety, confidence, authority, and intelligence. This will help your dog to be calm himself.

11. If you have more than one dog in your home, you decide the "pecking" order within the dog pack by routinely feeding the "top" dog first, giving that dog bones first, etc. Make the others wait for their turn. This is another means of exerting your authority.

Your Dog Will be Happier

You may think that this system is just being too controlling and not "fair" to the dog. Actually, by being consistent in your handling and in your demands on the dog you are being fair. He needs structure - to understand what you want and what his responsibilities are. What is truly unfair is giving up a dog because of behavior problems - problems caused by the lack of structure and guidance that were the owners' responsibility to give. Unfortunately, animal shelters are filled every day with these dogs. Firm, loving training will keep you and your dog happy - and keep you together.

- C.A.R.E.S. Companion Animal Resource & Education Society (Schenectady, NY) & Progressive Animal Welfare Society

Email us


Mixed Berry Bread Pudding With Lemon Fondant (Tyler Florence)

Total Time
Prep 10 mins
Cook 25 mins

Adapted from a recipe by Tyler Florence in _Stirring the Pot_, as published at http://tinyurl.com/deb7f5 Original recipe calls for brioche; I put the challah first to get reasonable nutritional information (brioche is not in the database).

Ingredients Nutrition

  1. Preheat oven to 350°F Generously butter a large casserole dish, or 8 6-ounce ramekins. Pour in sugar, and rotate dish so all of the buttered surfaces are coated with sugar; knock out any excess sugar.
  2. In a medium bowl, whisk together eggs, milk, cream, vanilla, lemon zest and sugar, until well combined.
  3. Roughly tear bread into large pieces with your hands. Add bread to custard and stir to combine. Spread berries evenly over the bottom of the casserole, or divide amongst the prepared ramekins. Pour custard mixture into pan or divide amongst ramekins, and push down to submerge the bread. Sprinkle the top evenly with additional sugar, then refrigerate 10-15 minutes to soak.
  4. Bake in preheated oven 25 minutes, or until puffy, the custard is set, and the top is golden-brown. Set aside.
  5. In a mixing bowl, stir together confectioner's sugar, water, lemon zest and lemon juice, until smooth.
  6. When slightly cooled, if using individual ramekins, invert each pudding onto a serving plate; otherwise, simply dish a portion onto each plate. Drizzle pudding with lemon fondant. Serve with additional fresh berries.


How Rising Interest Rates Could Affect Your Portfolio
Life + Leisure

How Rising Interest Rates Could Affect Your Portfolio

How much of an increase and when it actually occurs will be based on labor market conditions, inflation indicators, and other financial developments. The better the economy does, the sooner and faster the Fed will increase rates – which follows the Fed’s recent decision to end quantitative easing, the bond-buying program that bolstered the economy and stimulated the stock market, which has risen about 131 percent.

Many investors wonder what impact rising interest rates will have on their portfolios and what strategies can best help them navigate a potentially volatile period.

“Investors, especially those seeking current income, need to consider not only the probability of rising rates but also the probability that rates, even if rising, could remain at historical lows for a long time,” says David Bruckman, managing director at Citrin Cooperman Wealth Management, a New York-based accounting firm.

There’s no one-size-fits-all answer, but here are some tips that can help you think about the best moves. Remember not to make any moves based on current headlines, but rather on a long-term strategy meant to withstand the market’s inherent ups and downs.

A rise in rates can do significant harm to bond assets, but advisors don’t recommend investors unload all of their bonds. Short duration bonds are less susceptible to interest rates moves, and high-quality tax-free municipal bonds might be a good move for more conservative investors.

Related: 3 Steps to a More Fed-Proof Portfolio

Bruckman of Citrin Cooperman says that the rise in interest rates is less important if buyers of individual bonds plan to hold them to maturity. For investors who purchase bond funds, ETFs and actively managed mutual funds are a good solution.

For clients seeking current income, look for funds that focus on high-yield bonds, floating-rate notes, and international bonds. Short-term bond funds are a good hedge against the blow of potentially rising interest rates, Bruckman advises.

Another option: so-called unconstrained bond funds that allow managers the leeway to diversify positions in order to react to the market.

“For certain clients, treasury inflation protected securities (TIPS) should help over time to insulate a diversified portfolio against persistent rising rates, assuming such increases are accompanied by an increase in inflation,” says Bruckman.

Related: 3 Strategies for Making Your Retirement Money Last

Clare Sheridan, a former financial advisor at Morgan Stanley, says investors with a really strong conviction about rates going up might buy a floating-rate note: Its rate varies with market movement. She doesn’t believe that investors who want to generate income should be drastically changing their bond exposure.

“If you are trying to hedge against the stock market going down, then you’ll probably be in a longer-duration fixed-income bond,” Sheridan says. “If you just want to preserve capital, you’d be in a short, pretty safe, not very exciting investment.”

It’s more difficult to predict the impact increasing interest rates will have on equities, since so many factors influence how the market behaves. “The higher rates over the near term tend to have negative impact on the stock market, but if you look out at longer period of times, it’s actually a benefit,” says Michael Sabatino, managing director at McGraw-Hill Federal Credit Union.

When investors become frightened by the possibility of inflation, he says, that tends to create more market volatility — but in long-term cycles, owning stock is a way to protect against inflation.

Related: 6 Smart Ways to Get Ahead of Rising Interest Rates

Sarah Carlson, a private wealth manager at Fulcrum Financial Group in Spokane, Washington, recommends clients pursue high quality dividend-paying stocks. She’s looking at opportunities in health care and technology as bright spots that will continue to be sectors of what she calls American dominance.

If your stock holdings have grown disproportionately to the rest of your portfolio (they probably have), now might be a good time to take your profits and rebalance.

For those able to take on more risk, commodity trading and broad-based metals tend to rise with inflation and could serve as another hedge to rising rates.

Other potential alternative investments include master limited partnerships (MLPs), which are publically traded partnerships usually involved in real estate, petroleum and natural gas extraction businesses; absolute return funds, where managers have more discretion about the type of asset classes they can invest in; and real estate investment trusts (REITs). Investing a small portion of your portfolio in these investments could be a good move, but as always, check with a trusted advisor beforehand.

Related: Not Ready for Retirement? That’s a Problem

For retirees who need a fixed income, annuities may make sense and offer the peace of mind that comes with guaranteed income. “For older clients, an immediate annuity will offer considerably greater cash flow than that from a traditional fixed income portfolio,” Bruckman says.

After years of offering paltry returns, these old standbys could actually start to collect some interest. “Older folks who own CDs would benefit from the additional rate,” says Michael Sabatino of the McGraw-Hill Federal Credit Union. “It would be a positive for retirees generally who have these fixed income instruments which would generate more yield.”

Top Reads from The Fiscal Times:


The Chemistry of Genius?

Posted on February 1, 2012 by

New Science on What Makes Quality Education
by Oliver DeMille

Harvard Business School recently emphasized that the major changes in the world tend to come from what they called “disruptive innovators.”

These are surprising innovations that usually come from out-of-the-mainstream sources and drastically change society, business, and other facets of life.

Disruptive innovators are disruptive precisely because they are totally unexpected by the mainstream.

Malcolm Gladwell wrote a best-selling book* on the concept, showing that many and in fact most of the major societal initiators come from “outliers.”

Why are so many progresses initiated and led by unknown talent hotbeds, what Daniel Coyle called “chicken-wire Harvards”?

Indeed, Harvard, Yale, Stanford and their counterparts may lead the analysis about innovations, but “chicken-wire Harvards” produce many more innovative projects.

The Innovation “Gene”

Why is more entrepreneurial, innovative and leadership education flourishing in small, humble, usually under-funded environments than in the prestigious, elite halls of endowments and status?

And even when the mainstream and elite institutions take note and attempt to emulate such successes, why do they usually fall short of the smaller talent hotbeds?

The answer is simple. The breeding grounds of initiative and leadership believe in and implement the philosophy of individualized education.

Nearly everywhere else, the emphasis is on systematized models of learning that students must learn to navigate and “fit.”

To reinforce this point, there are many small, humble and under-funded educational models that are not talent hotbeds—almost invariably they are followers of the “systems model” rather than individualization.

Dead Poet’s Society

I well remember a visit years ago to a private school that had just received two major breakthroughs: an endowment from a wealthy parent, and a new president who promised to significantly grow the school.

As I talked to this president, however, I realized that he fully intended to turn this excellent, proven hotbed of talent into a systematized conveyor belt. He felt that this is what the wealthy donor wanted, and maybe it was.

But I could tell after a few minutes of visiting with him that he would ruin the depth, quality and excellent results the school had boasted for the past decade.

Five years later, my worst concerns were unfortunately the reality. The school was no longer a place of deep quality and excellence, but it was much bigger, more bureaucratic, and hardly distinguishable from the local public schools. Indeed, several charter schools in the area offered much higher quality.

The key to this change was teachers. In the public schools, teachers have been penalized for great teaching since 2002. As Harper’s noted:

“Under the No Child Left Behind Act of 2002…U.S. teachers are forced to choose between teaching general knowledge and ‘teaching to the test.’ The best teachers are thereby often disenfranchised by the improper use of education information systems.”

But in private schools, this system is not mandated. However, when such schools apply the systems approach to education, they usually obtain similar mediocre results.

In the old, under-funded days of this high school, the teachers had given their hearts and souls to provide personalized, individualized attention to every student.

As the school turned to industrial systems, these teachers were forced to move on or change their approach from individualized learning to factory-style academia.

Approaching each child with the assumption that she has genius inside, and that the teacher’s role is to help her find it, develop and polish it to improve herself and the world—this is called teaching. Anything else is something else.

Where true teaching occurs, excellence flourishes. This is applicable at all levels, from elementary to high school, undergraduate to graduate programs, and also adult learning.

Individualization of education is the first step to leadership education, and without it quality always decreases.

Seratonin, Adrenaline and Myelin

Science is now beginning to show the reasons why quality in education increases with individualization.

Studies have shown for a long time that students receiving personalized, caring and quality mentorship learn more effectively than those required to conform to a deeply structured and systemized model.

Elites have historically been successful in engaging tutors, mentors and individualizing private schools over less personal conveyor-belt schooling options.

cientists are now discovering that the individualized method (personalized mentoring, deep practice, long hours of inspired and enthusiastic academic effort) results in drastically higher levels of the neural insulator myelinthan the standardized system of education.

Students with higher levels of myelin learn more and remember it longer. It is especially valuable for gaining, maintaining and polishing skills.

As Daniel Coyle writes in The Talent Code:

“The talent code is built on revolutionary scientific discoveries involving a neural insulator called myelin, which some neurologists now consider to be the holy grail of acquiring skill. Here’s why. Every human skill…is created by chains of nerve fibers carrying a tiny electrical impulse—basically, a signal traveling through a circuit.

“Myelin’s vital role is to wrap those nerve fibers the same way that rubber insulation wraps a copper wire, making the signal stronger and faster…each new layer adding a bit more skill and speed.”

This research is in its infancy, but it is already helping us understand that there are neuro-chemical factors in our basic psycho-physiology that are impacted by our learning environment.

Montessori, Charlotte Mason and other great educators have taught this for many years.

Personalized educational models, with dedicated and caring mentors helping learners achieve depth and inspiration in their studies, achieve better results than assembly-line education.

Mentoring Matters

Quality mentors help students learn at least three key things:

  1. How to see their internal greatness and potential.
  2. How to study and practice in ways that greatly increase the flow of learning.
  3. How to repeat this kind of learning experience at will.

These are nearly always individualized lessons; and when they are applied, researchers are finding, the level of myelin and the resultant quality of learning increases.

To increase myelin levels and create talent hotbeds, Coyle says, mentors must create an environment of individualized coaching, be perceptive in seeing individual needs in their students, use shock or intensity to open student minds and then share valuable information, and find ways to really connect with each learner.

All of this is traditional leadership education, based on the same principles as the 7 Keys covered in my book A Thomas Jefferson Education:

  1. Classics, not Textbooks
  2. Mentors, not Professors
  3. Inspire, not Require
  4. Structure Time, not Content
  5. Quality, not Conformity
  6. Simplicity, not Complexity
  7. You, not Them (example)

It would be interesting to study the myelin levels of each. Say, for example, a study of myelin levels in students whose teachers emphasize the “inspire” approach versus those with more “requirement-oriented” methods. There could be many other examples.

Individualization Breeds Innovation

One thing is clear, if not yet scientifically studied: Most parents and teachers who apply the 7 Keys see significant, drastic and lasting increases in the quality of their students’ and their own learning.

Personalized education is more effective in helping students learn in their areas of interest, and it also outperforms generally in math, science and technology.

In the decades ahead, as in decades past, many of the most innovative ideas and projects are likely to come from talent hothouses outside the mainstream—places where dedicated and caring mentors help young people see their huge potential, start to discover their great inner genius, and feel inspired to do the hard and effective work of getting a great education.

Individualized, mentored, intensive learning has better results than standardized, rote and minimum-standards systems.

Click Here to Download a PDF of this Article

*A portion of the proceeds from amazon purchases originating from links in this article help support TJEd. Thanks for starting your amazon shopping at!

Posted in: Answering


Greener Ideal
Greener Ideal

Study Shows: U.S. East Coast Sea Temperatures Highest In 150 Years

Susmita BaralSusmita Baral

By Susmita Baral Susmita Baral |

NOAA’s Northeast Fisheries Science Center (NEFSC) has reported that the U.S. east coast sea surface temperatures had the warmest year in 2012 in the past 150 years.

The researchers analyzed temperatures between Cape Hatteras, N.C. and the Gulf of Maine using satellite and ship-board measurements. They found that the average sea surface temperature reached  57.2 F (14 C) in 2012, which beat the previous highest record set in 1951.

“2012’s temperature rise also marked the largest single-year increase since records began in 1854 and one of only five times that average temperatures have jumped by more than 1.8 F (1 C),” writes the Huffington Post.

“Changes in ocean temperatures and the timing and strength of spring and fall plankton blooms could affect the biological clocks of many marine species, which spawn at specific times of the year based on environmental cues like water temperature,” Kevin Friedland, a scientist in the NEFSC Ecosystem Assessment Program, said in a press statement.

The Huffington Post shares:

Research has shown that rising ocean temperatures as a result of climate change may also pose a threat to the ocean’s single-celled phytoplankton, such as algae. They are not only the foundation of the marine food chain, Climate Central explains, but they also “consume about half of the carbon dioxide that enters the atmosphere.”

Scientists aren’t certain of the extent to which rising temperatures will impact these organisms, or how quickly they will be able to adapt, but slowed phytoplankton growth could mean more CO2 remaining in the atmosphere.

Atmospheric CO2 concentrations are at their highest level in human history and continue to rise.

Increased carbon dioxide in the air — as a result of human activities like the burning of fossil fuels — also means more CO2 dissolved in the world’s oceans.

“It’s yet another reason to be very seriously concerned about the amount of carbon dioxide that is in the atmosphere now and the additional amount we continue to put out,” NOAA chief Jane Lubchenco told the Associated Press in 2012. “It is going to be a long time before we can stabilize and turn around the direction of change simply because it’s a big atmosphere and it’s a big ocean.”

Related:   Will British Summers Get Worse Over the Next 20 Years?

The study’s lead author, Sefan Rahmstorf, of the Potsdam (Germany) Institute for Climate Impact Research shares:

Wondering how different the two projections are? The IPCC projected that sea level rise is happening at the rate of 2mm per year, whereas the new research estimates that sea levels are rising at an average rate of 3.2mm a year. What’s more, these findings don’t even account for the ice flowing into the sea from Greenland and Antarctica.

Harvey Barrison


Cabling Installation Maintenance Magazine

I just wanted to share a useful magazine I have found which I thought had a lot of good information regarding Cabling Infrastructures. It is called Cabling Installation and Maintenance.

They have many Webinars which focus or highlight various manfucturers or technologies which is a good place to start to learn new areas of interests.

I am not anyway associated with the magazine. As an end user, I just wanted to share what I find useful in my day to day work.

Enjoy the link.

Login to read this IPVM discussion.
Why do I need to log in?

** ***** ******, ***** **** * ****** ****-**** ****. ****** for *** ****!


1 / 21

Gabriel Garcia Marquez

Gabriel Garcia Marquez

Yahoo News

A person close to the family has confirmed reports that that Nobel laureate Gabriel Garcia Marquez has died. He was 87.

Garcia Marquez's magical realist novels and short stories exposed tens of millions of readers to Latin America's passion, superstition, violence and inequality. Widely considered the most popular Spanish-language writer since Miguel de Cervantes in the 17th century, Garcia Marquez achieved literary celebrity that spawned comparisons to Mark Twain and Charles Dickens. (AP)


Project AGI

Building an Artificial General Intelligence

Tuesday, 20 September 2016

Region-Layer Experiments

Typical results from our experiments: Some active cells in layer 3 of a 3 layer network, transformed back into the input pixels they represent. The red pixels are positive weights and the blue pixels are negative weights; absence of colour indicates neutral weighting (ambiguity). The white pixels are the input stimulus that produced the selected set of active cells in layer 3. It appears these layer 3 cells collectively represent a generic '5' digit. The input was a specific '5' digit. Note that the weights of the hidden layer cells differ from the input pixels, but are recognizably the same digit.
We are running a series of experiments to test the capabilities of the Region-Layer component. The objective is to understand to what extent these ideas work, and to expose limitations both in implementation and theory.

Results will be posted to the blog and written up for publication if, or when, we reach an acceptable level of novelty and rigor.

We are not trying to beat benchmarks here. We’re trying to show whether certain ideas have useful qualities - the best way to tackle specific AI problems is almost certainly not an AGI way. But what we’d love to see is that AGI-inspired methods can perform close to state-of-the-art (e.g. deep convolutional networks) on a wide range of problems. Now that would be general intelligence!

Dataset Choice

We are going to start with the MNIST digit classification dataset, and perform a number of experiments based on that. In future we will look at some more sophisticated image / object classification datasets such as LabelMe or Caltech_101.

The good thing about MNIST is that it’s simple and has been extremely widely studied. It’s easy to work with the data and the images are a practical size - big enough to be interesting, but not so big as to require lots of preprocessing or too much memory. Despite only 28x28 pixels, variations in digit appearance gives considerable depth to the data (example digit '5' above).

The bad thing about MNIST is that it’s largely “solved” by supervised learning algorithms. A range of different supervised techniques have reached human performance and it’s debatable whether any further improvements are genuine.

So what’s the point of trying new approaches? Well, supervised algorithms have some odd qualities, perhaps due to the narrowness of training samples or the specificity of the cost function. For example, the discovery of “adversarial examples” - images that look easily classifiable to the naked eye but cannot be classified correctly with a trained network because they exploit weaknesses in trained neural networks.

But the biggest drawback of supervised learning is the need to tell it the “correct” answer for every input. This has led to a range of techniques - such as transfer learning - to make the most of what training data is available, even if not directly relevant. But fundamentally, supervised learning is unlike the experience of an agent learning as it explores its world. Animals can learn without a tutor.

However, unsupervised results with MNIST are less widely reported. Partially this is because you need to come up with a way to measure the performance of an unsupervised method. The most common approach is to use unsupervised networks to boost the performance of a final supervised network layer - but in MNIST the supervised layer is so powerful it’s hard to distinguish the contribution of the unsupervised layers. Nevertheless, these experiments are encouraging because having a few unsupervised layers seems to improve overall performance, compared to all-supervised networks. In addition to the limited data problem with supervised learning, unsupervised learning actually seems to add something.

One possible method of capturing the contribution of unsupervised layers alone is the Rand Index, which measures the similarity between two clusters. However, we are intending to use a distributed representation where there will be overlap between similar representations - that’s one of the features of the algorithm!

So, for now we’re going to go for the simplest approach we can think of, and measure the correlation between the active cells in selected hidden layers and each digit label, and see if the correlation alone is enough to pick the right label given a set of active cells. If the concepts defined by the digits exist somewhere in the hierarchy, they should be detectable as features uniquely correlated with specific labels...

Note also that we’re not doing any preprocessing of the MNIST images except binarization at threshold 0.5. Since the MNIST dataset is very high contrast, hopefully the threshold doesn’t matter much: It’s almost binary already.

Sequence Learning Tests

Before we start the experiments proper we conducted some ad-hoc tests to verify the features of the Region-Layer are implemented as intended. Remember, the Region-Layer has two key capabilities:

  • Classification … of the feedforward input, and
  • Prediction … of future classification results (i.e. future internal states)

See here and here to understand the classification role, and here for more information about prediction. Taken together, the ability to classify and predict future classifications allows sequences of input to be learned. This is a topic we have looked at in detail in earlier blog posts and we have some fairly effective techniques at our disposal.

We completed the following tests:

  • Cycle 0,1,2: We verified that the algorithm could predict the set of active cells in a short cycle of images. This ensures the sequence learning feature is working. The same image was used for each instance of a particular digit (i.e. there was no variation in digit appearance).
  • Cycle 0,1,...,9: We tested a longer cycle. Again, the Region-Layer was able to predict the sequence perfectly.
  • Cycle 0,1,2,3, 0,2,3,1: We tested an ambiguous cycle. At 0, it appears that the next state can be 1 or 2, and similarly, at 3, the next state can be 1 or 2. However, due to the variable order modelling behaviour of the Region-Layer, a single Region-Layer is able to predict this cycle perfectly. Note that first-order prediction cannot predict this sequence correctly.
  • Cycle 0,1,2,3,1,2,4,0,2,3,1,2,1,5,0,3,2,1,4,5: We tested a complex graph of state sequences and again a single Region-Layer was able to predict the sequence perfectly. We also were able to predict this using only first order modelling and a deep hierarchy.

After completion of the unit tests we were satisfied that our Region-Layer component has the ability to efficiently produce variable order models of observed sequences using unsupervised learning, assuming that the states can reliably be detected.

Now we come to the harder part. What if each digit exemplar image is ambiguous? In other words, what if each ‘0’ is represented by a randomly selected ‘0’ image from the MNIST dataset? The ambiguity of appearance means that the observed sequences will appear to be non-deterministic.

We decided to run the following experiments:

Experiment 1: Random image classification

In this experiment there will be no predictable sequence; each digit must be recognized solely based on its appearance. The classic experiment is used: Up to N training passes over the entire MNIST dataset, followed by fixing the internal weights and a single pass to calculate the correlation between each active cell in selected hidden layer[s] and the digit labels. Then, a single pass over the test set recording, for each test input image, the most highly correlated digit label for each set of active hidden cells. The algorithm gets a “correct” result if the most correlated label is the correct label.

  • Passes 1-N: Train networks

Present each digit in the training set once, in a random order. Train the internal weights of the algorithm. Repeated several times if necessary.

  • Pass N+1: Measure correlation of hidden layer features with training images.

Present each digit in the training set once, in a random order. Accumulate the frequency with which each active cell is associated with each digit label. After all images have been seen, convert the observed frequencies to correlations.

  • Pass N+2: Predict label of test images.

Present each digit in the testing set once, in a random order. Use the correlations between cell activity and training labels to predict the most likely digit label given the set of active cells in selected Region-Layer components (they are arranged into a hierarchy).

Experiment 2: Image classification & sequence prediction

What if the digit images are not in a random order? We can use the English language to generate a training set of digit sequences. For example, we can get a book, convert each character to a 2 digit number and select random appropriate digit images to represent each number.

The motivation for this experiment is to see how the sequence learning can boost image recognition: Our Region-Layer component is supposed to be able to integrate both sequential and spatial information. This experiment actually has a lot of depth because English isn’t entirely predictable - if we use a different book for testing, there’ll be lots of sub-sequences the algorithm has never observed before. There’ll be uncertainty in image appearance and uncertainty in sequence, and we’d like to see how a hierarchy of Region-Layer components responds to both. Our expectation is that it will improve digit classification performance beyond the random image case.

In the next article, we will describe the specifics of the algorithms we implemented and tested on these problems.

A final article will present some results.

Friday, 9 September 2016

The Region-Layer: A building block for AGI

Introducing the Region-Layer

We assume the Region-Layer is trained by unsupervised learning only - it finds structure in its input without caring about associated utility or rewards. Learning should be continuous and online, learning as an agent from experience. It should adapt to non-stationary input statistics at any time.

So let's put our cards on the table and test these ideas.

Region-Layer Implementation

  • RW: Width of region layer in Columns
  • RH: Height of region layer in Columns
  • CW: Width of column in Cells
  • CH: Height of column in Cells

Inputs and Outputs

+  Region Area = CW * CH * RW * RH

    function: UpdateAndTrain(

    // if no active input, then do nothing
    if( sum( input ) == 0 ) {

    // Sparse activation

    activity(t) = 0

    for-each( column c ) {
      // find cell x that most responds to FFI
      // in current sequential context given:
      //  a) prior active cells in region
      //  b) feedback input.
      x = findBestCellsInColumn( feed_forward_input, feed_back_input, c )

      activity(t)[ x ] = 1

    // Change detection
    // if active cells in region unchanged, then do nothing

    // Update receptive fields to organize columns
    trainReceptiveFields( feed_forward_input, columns )

    // Update cell weights given column receptive fields
    // and selected active cells
    trainCells( feed_forward_input, feed_back_input, activity(t) )

    for-each( cell x in region-layer ) {

      coding = 0

        coding = 1

        coding = 0

      output(t)[x] = coding

    // Update prediction
    // context in the active cell selection step.
    prediction(t) = predict( activity(t) )

    [2] https://papers.nips.cc/paper/893-a-growing-neural-gas-network-learns-topologies.pdf
    [3] http://www.cs.bham.ac.uk/~jxb/NN/l16.pdf
    [4] https://arxiv.org/pdf/1312.5663
    [5] http://www.ncbi.nlm.nih.gov/pubmed/10195184

    Wednesday, 18 May 2016

    Reading list - May 2016

    Digit classification error over time in our experiments. The image isn't very helpful but it's a hint as to why we're excited :)

    Project AGI

    A few weeks ago we paused the "How to build a General Intelligence" series (part 1, part 2, part 3, part 4). We paused it because the next article in the series requires us to specify everything in detail, and we need working code to do that.

    We have been testing our algorithm on a variety of MNIST-derived handwritten digit datasets, to better understand how well it generalizes its representation of digit-images and how it behaves when exposed to varying degrees of predictability. Initial results look promising: We will post everything here once we've verified them and completed the first batch of proper experiments. The series will continue soon!

    Deep Unsupervised Learning

    Our algorithm is a type of Online Deep Unsupervised Learning, so naturally we're looking carefully at similar algorithms.

    We recommend this video of a talk by Andrew Ng. It starts with a good introduction to the methods and importance of feature representation and touches on types of automatic feature discovery. He looks at some of the important feature detectors in computer vision, such as SIFT and HoG and shows how feature detectors - such as edge detectors - can emerge from more general pattern recognition algorithms such as sparse coding. For more on sparse coding see Shakir's excellent machine learning blog.

    For anyone struggling to intuit deep feature discovery, I also loved this post on yCombinator which nicely illustrates how and why deep networks discover useful features, and why the depth helps.

    The latter part of the video covers Ng's latest work on deep hierarchical sparse coding using Deep Belief Networks, in turn based on AutoEncoders. He reports benchmark-beating results on video activity and phoneme recognition with this framework. You can find details of his deep unsupervised algorithm here:

    Finally he presents a plot suggesting that training dataset size is a more important determiner of eventual supervised network performance than algorithm choice! This is a fundamental limitation of supervised learning where the necessary training data is much more limited than in unsupervised learning (in the latter case, the real world provides a handy training set!)

    Effect of algorithm and training set size on accuracy. Training set size more significant. This is a fundamental limitation of supervised learning.

    Online K-sparse autoencoders (with some deep-ness)

    We've also been reading this paper by Makhzani and Frey about deep online learning with auto-encoders (a type of supervised learning neural network that is used in an unsupervised way to reconstruct its input, often known as semi-supervised learning). Actually we've struggled to find any comparison of autoencoders to earlier methods of unsupervised learning both in terms of computational efficiency and ability to cover the search space effectively. Let us know if you find a paper that covers this.

    The Makhzani paper has some interesting characteristics - the algorithm is online, which means it receives data as a stream rather than in batches. It is also sparse, which we believe is desirable from a representational perspective.

    One limitation is that the solution is most likely unable to handle changes in input data statistics (i.e. non-stationary problems). The reason this is an important quality is that in any arbitrarily deep network the typical position of a vertex is between higher and lower vertices. If all vertices are continually learning, the problem being modelled by any single vertex is constantly changing. Therefore, intermediate vertices must be capable of online learning of non stationary problems otherwise the network will not be able to function effectively. In Makhzani and Frey, they instead use the greedy layerwise training approach from Deep Belief Networks. The authors describe this approach:

    "4.6. Deep Supervised Learning Results The k-sparse autoencoder can be used as a building block of a deep neural network, using greedy layerwise pre-training (Bengio et al., 2007). We first train a shallow k-sparse autoencoder and obtain the hidden codes. We then fix the features and train another ksparse autoencoder on top of them to obtain another set of hidden codes. Then we use the parameters of these autoencoders to initialize a discriminative neural network with two hidden layers."

    The limitation introduced can be thought of as an inability to escape from local minima that result from prior training. This paper by Choromanska et al tries to explain why this happens.

    Greedy layerwise training is an attempt to work around the fact that deep belief networks of Autoencoders cannot effectively handle nonstationary problems.

    For more information here's some papers on deep sparse networks built from autoencoders:

    Variations on Supervised Learning - a Taxonomy

    Back to supervised learning, and the limitation of training dataset size. Thanks to a discussion with Jay Chakravarty we have this brief taxonomy of supervised learning workarounds for insufficient training datasets:

    Weakly supervised learning: [For poorly labelled training data] where you want to learn models for object recognition under weak supervision - you have say object labels for images, but no localization (e.g. bounding box) for the object in the image (there might be other objects in the image as well). You would use a Latent SVM to solve the problem of localizing the objects in the images, and at the same time learning a classifier for it.

    Another example of weakly supervised learning is that you have a bag of positive samples mixed up with negative training samples, but also have a bag of purely negative samples - you would use Multiple Instance Learning for this.

    Cross-modal adaptation: where one mode of data supervises another - e.g. audio supervises video or vice-versa.

    Domain adaptation: model learnt on one set of data is adapted, in unsupervised fashion, to new datasets with slightly different data distributions.

    Transfer learning: using the knowledge gained in learning one problem on a different, but related problem. Here's a good example of transfer learning, a finalist in the NVIDIA 2016 Global Impact Award. The system learns to predict poverty from day and night satellite images, with very few labelled samples.

    Full paper:

    Interactive Brain Concept Map

    We enjoyed this interactive map of the distribution of concepts within the cortex captured using fMRI and produced by the Gallant Lab (source papers here).

    Using the map you can find the voxels corresponding to various concepts, which although maybe not generalizable due to the small sample size (7) gives you a good idea of the hierarchical structure the brain has produced, and what the intermediate concepts represent.

    Thanks to David Ray @ http://cortical.io for the link.

    Interactive brain concept map

    OpenAI Gym - Reinforcement Learning platform

    We also follow the OpenAI project with interest. OpenAI have just released their "Gym" - a platform for training and testing reinforcement learning algorithms. Have a play with it here:

    According to Wired magazine, OpenAI will continue to release free and open source software (FOSS) for the wider impact this will have on uptake. There are many companies now competing to win market share in this space.

    The Talking Machines Blog

    We're regular readers of this blog and have been meaning to mention it for months. Worth reading.

    How the brain generates actions

    A big gap in our knowledge is how the brain generates actions from its internal representation. This new paper by Vicente et al challenges the established (rather vague) dogma on how the brain generates actions.

    “We found that contrary to common belief, the indirect pathway does not always prevent actions from being performed, it can actually reinforce the performance of actions. However, the indirect pathway promotes a different type of actions, habits.”

    This is probably quite informative for reverse-engineering purposes. Full paper here.

    Hierarchical Temporal Memory

    HTM is an online method for feature discovery and representation and now we have a baseline result for HTM on the famous MNIST numerical digit classification problem. Since HTM works with time-series data, the paper compares HTM to LSTM (Long-Short-Term Memory), the leading supervised-learning approach to this problem domain.

    It is also interesting that the paper deals with adaptation to sudden changes in the input data statistics, the very problem that frustrates the deep belief networks described above.

    Full paper by Cui et al here.

    For a detailed mathematical description of HTM see this paper by Mnatzaganian and Kudithipudi.

    Wednesday, 23 March 2016

    Reading list: Assorted AGI links. March 2016

    A Minecraft API is now available to train your AGIs

    Our News

    Sharing places with robots

    Hierarchical Quilted Self-Organizing Maps & Distributed Representations

    Reinforcement Learning

    Long-Short-Term Memory (LSTM)

    Fun thoughts

    Thursday, 10 March 2016

    What's after AlphaGo?

    What's AlphaGo?

    AlphaGo is a system that can play Go at least as well as the best humans. Go was widely cited as the hardest (and only remaining) game at which humans could beat machines, so this is a big deal. AlphaGo has just defeated a top-ranked human expert.

    Why is Go hard?

    Go is hard because the search-space of possible moves is so large that tree search and pruning techniques, such as those used to beat humans at Chess, won't work - or at least, they won't work well enough, with a feasible amount of memory, to play Go better than the best humans.

    Instead, to play Go well, you need to have "intuition" rather than brute search power: To look at the board and spot local (or gross) patterns that represent opportunities or dangers. And in fact, AlphaGo is able to play in this way. It beat the next best computer algorithm "Pachi" 85% of the time without any tree search - just predicting the best action based on its interpretation of the current state. The authors of the AlphaGo Nature paper say:

    How does AlphaGo work?

    AlphaGo is trained by both supervised and reinforcement learning. Supervised learning feedback comes from recordings of moves in expert games. However, these are finite in size and used naively, would lead to overfitting

    Instead, in AlphaGo a Supervised Learning deep neural network learns to model and predict expert behaviour in the recorded games, via conventional deep learning techniques. Then, a reinforcement learning network is used to generate reward data for novel games that AlphaGo plays against itself! This mitigates the limited size of the supervised learning dataset.

    Of course, AlphaGo also wants the play better than the best play observed in the training data. To achieve this, the reinforcement learning network is further trained by playing pairs of them (networks) against each other - mixing the pairs up to prevent policies overfitting each other. This is a really clever feature because it allows AlphaGo to go beyond its training data.

    Note also that the neural networks cannot possibly fully represent a sufficiently deep tree of board outcomes within their limited set of weights. Instead, the network has to learn to represent good and bad situations with limited resources. It has to form its own representation of the most salient features, during training.

    The neural networks function without pre-defined rules specific to Go; instead they have learned from training data collected from many thousands of human and simulated games.

    Key advances

    AlphaGo is an important advance because it is able to make good judgments about play situations based on a lossy interpretation in a finitely-sized deep neural network.

    What’s more, Go wasn’t simply taught to copy human experts - it went further, and improved, by playing against itself.

    So, what doesn't it do?

    The techniques used in deep neural networks have recently been scaled to work effectively on a wide range of problems. In some subject areas, narrow AIs are reaching superhuman performance. However, it is not clear that these techniques will scale indefinitely. Problems such as vanishing gradients have been pushed back, but not necessarily eliminated.

    Much greater scale is needed to get intelligent agents into the real world without them being immediately smashed by cars or stuck in holes. But already, it is time to consider what features or characteristics constitute an artificial general intelligence (AGI), beyond raw intelligence (which AIs now have).

    AlphaGo isn't a general intelligence; it's designed specifically to play Go. Sure, it's trained rather than programmed manually, but it was designed for this purpose. The same techniques are likely to generalize to many other problems, but they'll need to be applied thoughtfully and retrained.

    AlphaGo isn't an Agent. It doesn't have any sense of self, or intent, and its behaviour is pretty static - its policies would probably work the same way in all similar situations, learning only very slowly. You could say that it doesn't have moods, or other transient biases. Maybe this is a good thing! But this also limits its ability to respond to dynamic situations.

    AlphaGo doesn't have any desire to explore, to seek novelty or to try different things. AlphaGo couldn't ever choose to teach itself to play Go because it found it interesting. On the other hand, AlphaGo did teach itself to play Go…

    All in all, it's a very exciting time to study artificial intelligence!

    by David Rawlinson & Gideon Kowadlo

    Tuesday, 9 February 2016

    Some interesting finds: Acyclic hierarchical modelling and sequence unfolding

    This week we have a couple of interesting links to share.

    From our experiments with generative hierarchical models, we claimed that the model produced by feed-forward processing should not have loops. Now we have discovered a paper by Bengio et al titled "Towards biologically plausible deep learning" [1] that supports this claim. The paper looks for biological mechanisms that mimic key features of deep learning. Probably the credit assignment problem is the most difficult feature to substantiate - ensuring each weight is updated correctly in response to its contribution to the overall output of the network - but the paper does leave me thinking it's plausible.

    Anyway the reason I'm talking about it is this quote:

    "There is strong biological evidence of a distinct pattern of connectivity between cortical areas that distinguishes between “feedforward” and “feedback” connections (Douglas et al., 1989) at the level of the microcircuit of cortex (i.e., feedforward and feedback connections do not land in the same type of cells). Furthermore, the feedforward connections form a directed acyclic graph with nodes (areas) updated in a particular order, e.g., in the visual cortex (Felleman and Essen, 1991)."

    This says that the feedforward modelling process (which we believe is constructing a hierarchical model) is a directed acyclic graph (DAG) - which means it does not have loops, as we predicted. Secondly, it is another source claiming that the representation produced is hierarchical (in this case, a DAG). The cited work is a much older paper - "Distributed hierarchical processing in the primate cerebral cortex" [2]. We're still reading, but there's a lot of good background information here.

    The second item to look at this week is a demo by Felix Andrews featuring temporal pooling [3] and sequence unfolding. "Unfolding" means transforming the pooled sequence representation back into its constituent parts - i.e. turning a sequence into a series of steps.

    Felix demonstrates that high-level sequence selection can successfully be used to track and predict through observation of the corresponding lower-level sequence. This is achieved by causing the high-level sequence to predict all steps, and then tracking through the predicted sequence using first-order predictions in the lower level. Both levels are necessary - the high level prediction provides guidance for the low-level to ensure it predicts correctly through forks. The low level prediction keeps track of what's next in the sequence.

    [1] "Towards Biologically Plausible Deep Learning" Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein and Zhouhan Lin (2015) http://arxiv.org/pdf/1502.04156v2.pdf

    [2] "Distributed hierarchical processing in the primate cerebral cortex" Felleman DJ, Van Essen DC (1991) http://www.ncbi.nlm.nih.gov/pubmed/1822724

    [3] Felix Andrews HTM temporal pooling and sequence unfolding demo http://viewer.gorilla-repl.org/view.html?source=gist&id=95da4401dc7293e02df3&filename=seq-replay.clj

    Wednesday, 3 February 2016

    Intuition over reasoning for AI

    By Gideon Kowadlo

    I’m reading a fascinating book called The Righteous Mind, by Jonathan Haidt. It’s one of those reads that can fundamentally shift the way that you see the world. In this case, the human world, everyone around you, and yourself.

    A central idea of the book is that our behaviour is mainly dictated by intuition rather than reasoning and that both are aspects of cognition.

    Many will be able to identify in themselves and others, the tendency to act first and rationalise later - even though it feels like the opposite. But more than that, our sense of morality arises from intuition and it enables us to act quickly and make good decisions.

    A compelling biological correlate is the ventromedial prefrontal cortex. The way it enables us to use emotion/intuition for decision making is described well in this passage:

    Damasio had noticed an unusual pattern of symptoms in patients who had suffered brain damage to a specific part of the brain - the ventromedial (i.e., bottom-middle) prefrontal cortex (abbreviated vmPFC; it’s the region just behind and above the bridge of the nose). Their emotionality dropped nearly to zero. They could look at the most joyous or gruesome photographs and feel nothing. They retained full knowledge of what was right and wrong, and they showed no deficits in IQ. They even scored well on Kohlberg’s tests of moral reasoning. Yet when it came to making decisions in their personal lives and at work, they made foolish decisions or no decisions at all. They alienated their families and their employers, and their lives fell apart.

    Damasio’s interpretation was that gut feelings and bodily reactions were necessary to think rationally, and that one job of the vmPFC was to integrate those gut feelings into a person’s conscious deliberations. When you weigh the advantages and disadvantages of murdering your parents … you can’t even do it, because feelings of horror come rushing in through the vmPFC.

    But Damasio’s patients could think about anything, with no filtering or coloring from their emotions. With the vmPFC shut down, every option at every moment felt as good as every other. The only way to make a decision was to examine each option, weighting the pros and cons using conscious verbal reasoning. If you’ve ever shopped for an appliance about which you have few feelings - say, a washing machine - you know how hard it can be once the number of options exceeds six or seven (which is the capacity of our short-term memory). Just imagine what your life would be like if at every moment, in every social situation, picking the right thing to do or say became like picking the best washing machine among ten options, minute after minute, day after day. You’d make foolish decisions too.

    Our aim has always been to build a general reasoning machine that can be scaled up. We aren’t interested in building an artificial human, which carries the legacy of a long evolution through many incarnations.

    This is the first time I’ve considered the importance of building intuition into the algorithm as a fundamental component. ‘Gut’ reactions are not to be underestimated. It may be the only way to make effective AGI, not to mention the need to create ‘pro-social’ agents with which we can interact in daily life.

    It is possible though, that this is an adaption to the limitations of our reasoning, rather than a fundamentally required feature. If the intelligence was implemented in silicon and not bound by 'cognitive effort' in the same way that we are, it could potentially select favourable actions efficiently based on intellectual reasoning, without the ‘intuition’.

    This is fascinating to think about in terms of human intelligence and behaviour. It raises exciting questions about the nature of intelligence itself and the relationship between cognition and both reasoning and intuition. We’ll be sure to consider these questions as we continue to develop an algorithm for AGI.

    From a functional perspective the vmPFC appears to be a separate parallel ‘component’ that is richly connected to many other brain areas.

     Wikipedia Ventromedial prefrontal cortex


Event: Persians Defeated at Plataea
Date: 479 B.C.
Place: Plataea
Brief Synopsis: Spartan Greeks, led by the generals Pausanias and Aristides, defeat Persian forces under General Mardonius. This defeat at Plataea signals the end of Persian occupation of Greek territory, which has been in place since the middle of the fifth century B.C. This military victory over the Persians gives the Greeks freedom to establish their own political and artistic culture.

Web Links

Brittanica.com’s “Greco-Persian Wars”

Boise State University’s History of Western Civilization

Warfare in Hellas

Dr. J’s Illustrated Persian Wars (scroll to find “Battle at Plataea”)

Research Questions

1. Where is Plataea? How does its location figure in what happened there? What happened at Plataea? Describe the events of the battle at Plataea.

2. Who were the major historical characters at the Battle of Plataea? Describe the historical context of the event (what came before and what came after in the historical chronology of the battle)?

3. How did the Persian Wars, especially the Battle at Plataea, unify the Hellenic city-states?

4. Describe the position of Persia in Asia Minor as a result of the battle at Plataea? What was the Delian League? Why was it formed and what was its purpose?

Team Discussion Question:

After your team has answered the questions above, discuss this question as a team:

· Who had the greater advantage in the war, the Persians or the Greeks?


The 2014 omnibus federal budget bill (Bill C-31) saw the introduction of legislation that would regulate dealers in virtual currencies as “money services businesses” under Canada’s Proceeds of Crime (Money Laundering) and Terrorist Financing Act. The implementing regulations are not yet published; however, June did see the release of Digital Currency: You Can’t Flip this Coin!, a report by the Senate Standing Committee on Banking, Trade and Commerce.

In the report, the senators recommend that “the federal government, in considering any legislation… create an environment that fosters innovation for digital currencies and their associated technologies.” The report also urges government to use a regulatory “light touch” to minimize “stifling” the development of payment, value storage and transmission technologies.

The report contains a concise and up-to-date overview of the principal issues, and has been welcomed as farsighted and forward-thinking by the digital currency (Bitcoin) community. It is worth paying attention to what is happening in the payments area, of which cryptocurrencies and blockchain technologies are a part.